Point spread function - Revision history

2601:14D:4D83:6C00:27:36F6:4FD4:9B28: fixed typo --> "shifting property" replaced with "sifting property"

2025-05-08T15:47:10Z

fixed typo --> "shifting property" replaced with "sifting property"

← Previous revision		Revision as of 15:47, 8 May 2025
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	[[Image:SquarePost.svg\|Square Post Function\|right\|thumb\|220px]]		[[Image:SquarePost.svg\|Square Post Function\|right\|thumb\|220px]]

	We imagine the object plane as being decomposed into square areas such as this, with each having its own associated square post function. If the height, ''h'', of the post is maintained at 1/w<sup>2</sup>, then as the side dimension ''w'' tends to zero, the height, ''h'', tends to infinity in such a way that the volume (integral) remains constant at 1. This gives the 2D impulse the ~~shifting~~ property (which is implied in the equation above), which says that when the 2D impulse function, δ(''x'' − ''u'',''y'' − ''v''), is integrated against any other [[continuous function]], {{nowrap\|''f''(''u'',''v'')}}, it "sifts out" the value of ''f'' at the location of the impulse, i.e., at the point {{nowrap\|(''x'',''y'')}}.		We imagine the object plane as being decomposed into square areas such as this, with each having its own associated square post function. If the height, ''h'', of the post is maintained at 1/w<sup>2</sup>, then as the side dimension ''w'' tends to zero, the height, ''h'', tends to infinity in such a way that the volume (integral) remains constant at 1. This gives the 2D impulse the sifting property (which is implied in the equation above), which says that when the 2D impulse function, δ(''x'' − ''u'',''y'' − ''v''), is integrated against any other [[continuous function]], {{nowrap\|''f''(''u'',''v'')}}, it "sifts out" the value of ''f'' at the location of the impulse, i.e., at the point {{nowrap\|(''x'',''y'')}}.

	The concept of a perfect point source object is central to the idea of PSF. However, there is no such thing in nature as a perfect mathematical point source radiator; the concept is completely non-physical and is rather a mathematical construct used to model and understand optical imaging systems. The utility of the point source concept comes from the fact that a point source in the 2D object plane can only radiate a perfect uniform-amplitude, spherical wave — a wave having perfectly spherical, outward travelling phase fronts with uniform intensity everywhere on the spheres (see [[Huygens–Fresnel principle]]). Such a source of uniform spherical waves is shown in the figure below. We also note that a perfect point source radiator will not only radiate a uniform spectrum of propagating plane waves, but a uniform spectrum of exponentially decaying ([[Evanescent wave\|evanescent]]) waves as well, and it is these which are responsible for resolution finer than one wavelength (see [[Fourier optics]]). This follows from the following [[Fourier transform]] expression for a 2D impulse function,		The concept of a perfect point source object is central to the idea of PSF. However, there is no such thing in nature as a perfect mathematical point source radiator; the concept is completely non-physical and is rather a mathematical construct used to model and understand optical imaging systems. The utility of the point source concept comes from the fact that a point source in the 2D object plane can only radiate a perfect uniform-amplitude, spherical wave — a wave having perfectly spherical, outward travelling phase fronts with uniform intensity everywhere on the spheres (see [[Huygens–Fresnel principle]]). Such a source of uniform spherical waves is shown in the figure below. We also note that a perfect point source radiator will not only radiate a uniform spectrum of propagating plane waves, but a uniform spectrum of exponentially decaying ([[Evanescent wave\|evanescent]]) waves as well, and it is these which are responsible for resolution finer than one wavelength (see [[Fourier optics]]). This follows from the following [[Fourier transform]] expression for a 2D impulse function,

Vsmith: Reverted edit by Nipun shantha (talk) to last version by VistaSegoe

2025-04-01T13:43:38Z

Reverted edit by Nipun shantha (talk) to last version by VistaSegoe

← Previous revision		Revision as of 13:43, 1 April 2025
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	the image of an object in a microscope or telescope as a non-coherent imaging system can be computed by expressing the object-plane field as a weighted sum of 2D impulse functions, and then expressing the image plane field as a weighted sum of the ''images'' of these impulse functions. This is known as the ''superposition principle'', valid for [[linear systems]]. The images of the individual object-plane impulse functions are called point spread functions (PSF), reflecting the fact that a mathematical ''point'' of light in the object plane is ''spread'' out to form a finite area in the image plane. (In some branches of mathematics and physics, these might be referred to as [[Green's functions]] or [[impulse response]] functions. PSFs are considered impulse response functions for imaging systems.		the image of an object in a microscope or telescope as a non-coherent imaging system can be computed by expressing the object-plane field as a weighted sum of 2D impulse functions, and then expressing the image plane field as a weighted sum of the ''images'' of these impulse functions. This is known as the ''superposition principle'', valid for [[linear systems]]. The images of the individual object-plane impulse functions are called point spread functions (PSF), reflecting the fact that a mathematical ''point'' of light in the object plane is ''spread'' out to form a finite area in the image plane. (In some branches of mathematics and physics, these might be referred to as [[Green's functions]] or [[impulse response]] functions. PSFs are considered impulse response functions for imaging systems.
	[[File:PSF Deconvolution V.png\|thumb\|265x265px\|Application of PSF: Deconvolution of the mathematically modeled PSF and the low-resolution image enhances the resolution.<ref name=Kiarash1>{{Cite journal \|last1=Ahi \|first1=Kiarash \|first2=Mehdi \|last2=Anwar \|editor3-first=Tariq \|editor3-last=Manzur \|editor2-first=Thomas W \|editor2-last=Crowe \|editor1-first=Mehdi F \|editor1-last=Anwar \|date=May 26, 2016 \|title=Developing terahertz imaging equation and enhancement of the resolution of terahertz images using deconvolution \|url=https://www.researchgate.net/publication/303563271 \|journal=Proc. SPIE 9856, Terahertz Physics, Devices, and Systems X: Advanced Applications in Industry and Defense, 98560N \|volume=9856 \|pages=98560N \|doi=10.1117/12.2228680\|series=Terahertz Physics, Devices, and Systems X: Advanced Applications in Industry and Defense \|bibcode=2016SPIE.9856E..0NA \|s2cid=114994724 }}</ref>]]		[[File:PSF Deconvolution V.png\|thumb\|265x265px\|Application of PSF: Deconvolution of the mathematically modeled PSF and the low-resolution image enhances the resolution.<ref name=Kiarash1>{{Cite journal \|last1=Ahi \|first1=Kiarash \|first2=Mehdi \|last2=Anwar \|editor3-first=Tariq \|editor3-last=Manzur \|editor2-first=Thomas W \|editor2-last=Crowe \|editor1-first=Mehdi F \|editor1-last=Anwar \|date=May 26, 2016 \|title=Developing terahertz imaging equation and enhancement of the resolution of terahertz images using deconvolution \|url=https://www.researchgate.net/publication/303563271 \|journal=Proc. SPIE 9856, Terahertz Physics, Devices, and Systems X: Advanced Applications in Industry and Defense, 98560N \|volume=9856 \|pages=98560N \|doi=10.1117/12.2228680\|series=Terahertz Physics, Devices, and Systems X: Advanced Applications in Industry and Defense \|bibcode=2016SPIE.9856E..0NA \|s2cid=114994724 }}</ref>]]
	When the object is divided into discrete point objects of varying intensity, the image is computed as a sum of the PSF of each point. As the PSF is typically determined entirely by the imaging system (that is, microscope or telescope), the entire image can be described by knowing the optical properties of the system. This imaging process is usually formulated by a [[convolution]] equation. In [[microscope image processing]] and [[astronomy]], knowing the PSF of the measuring device is very important for restoring the (original) object with [[deconvolution]]. For the case of laser beams, the PSF can be mathematically modeled using the concepts of [[Gaussian beam]]s <ref name="Kiarash2">{{Cite journal \|last1=Ahi \|first1=Kiarash \|first2=Mehdi \|last2=Anwar \|editor3-first=Tariq \|editor3-last=Manzur \|editor2-first=Thomas W \|editor2-last=Crowe \|editor1-first=Mehdi F \|editor1-last=Anwar \|date=May 26, 2016 \|title=Modeling of terahertz images based on x-ray images: a novel approach for verification of terahertz images and identification of objects with fine details beyond terahertz resolution \|url=https://www.researchgate.net/publication/303563365 \|journal=Proc. SPIE 9856, Terahertz Physics, Devices, and Systems X: Advanced Applications in Industry and Defense, 98560N \|volume=9856 \|page=985610 \|doi=10.1117/12.2228685\|series=Terahertz Physics, Devices, and Systems X: Advanced Applications in Industry and Defense \|bibcode=2016SPIE.9856E..10A \|s2cid=124315172 }}</ref>. For instance, deconvolution of the mathematically modeled PSF and the image, improves visibility of features and removes imaging noise <ref name="Kiarash1" />.		When the object is divided into discrete point objects of varying intensity, the image is computed as a sum of the PSF of each point. As the PSF is typically determined entirely by the imaging system (that is, microscope or telescope), the entire image can be described by knowing the optical properties of the system. This imaging process is usually formulated by a [[convolution]] equation. In [[microscope image processing]] and [[astronomy]], knowing the PSF of the measuring device is very important for restoring the (original) object with [[deconvolution]]. For the case of laser beams, the PSF can be mathematically modeled using the concepts of [[Gaussian beam]]s.<ref name=Kiarash2>{{Cite journal \|last1=Ahi \|first1=Kiarash \|first2=Mehdi \|last2=Anwar \|editor3-first=Tariq \|editor3-last=Manzur \|editor2-first=Thomas W \|editor2-last=Crowe \|editor1-first=Mehdi F \|editor1-last=Anwar \|date=May 26, 2016 \|title=Modeling of terahertz images based on x-ray images: a novel approach for verification of terahertz images and identification of objects with fine details beyond terahertz resolution \|url=https://www.researchgate.net/publication/303563365 \|journal=Proc. SPIE 9856, Terahertz Physics, Devices, and Systems X: Advanced Applications in Industry and Defense, 98560N \|volume=9856 \|page=985610 \|doi=10.1117/12.2228685\|series=Terahertz Physics, Devices, and Systems X: Advanced Applications in Industry and Defense \|bibcode=2016SPIE.9856E..10A \|s2cid=124315172 }}</ref> For instance, deconvolution of the mathematically modeled PSF and the image, improves visibility of features and removes imaging noise.<ref name=Kiarash1/>

	==Theory==		==Theory==
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	The figure above illustrates the truncation of the incident spherical wave by the lens. In order to measure the point spread function — or impulse response function — of the lens, a perfect point source that radiates a perfect spherical wave in all directions of space is not needed. This is because the lens has only a finite (angular) bandwidth, or finite intercept angle. Therefore, any angular bandwidth contained in the source, which extends past the edge angle of the lens (i.e., lies outside the bandwidth of the system), is essentially wasted source bandwidth because the lens can't intercept it in order to process it. As a result, a perfect point source is not required in order to measure a perfect point spread function. All we need is a light source which has at least as much angular bandwidth as the lens being tested (and of course, is uniform over that angular sector). In other words, we only require a point source which is produced by a convergent (uniform) spherical wave whose half angle is greater than the edge angle of the lens.		The figure above illustrates the truncation of the incident spherical wave by the lens. In order to measure the point spread function — or impulse response function — of the lens, a perfect point source that radiates a perfect spherical wave in all directions of space is not needed. This is because the lens has only a finite (angular) bandwidth, or finite intercept angle. Therefore, any angular bandwidth contained in the source, which extends past the edge angle of the lens (i.e., lies outside the bandwidth of the system), is essentially wasted source bandwidth because the lens can't intercept it in order to process it. As a result, a perfect point source is not required in order to measure a perfect point spread function. All we need is a light source which has at least as much angular bandwidth as the lens being tested (and of course, is uniform over that angular sector). In other words, we only require a point source which is produced by a convergent (uniform) spherical wave whose half angle is greater than the edge angle of the lens.

	Due to intrinsic limited resolution of the imaging systems, measured PSFs are not free of uncertainty <ref>{{Cite journal\|last1=Ahi\|first1=Kiarash\|last2=Shahbazmohamadi\|first2=Sina\|last3=Asadizanjani\|first3=Navid\|date=July 2017 \|title=Quality control and authentication of packaged integrated circuits using enhanced-spatial-resolution terahertz time-domain spectroscopy and imaging\|url=https://www.researchgate.net/publication/318712771\|journal=Optics and Lasers in Engineering\|volume=104\|pages=274–284\|doi=10.1016/j.optlaseng.2017.07.007\|bibcode=2018OptLE.104..274A}}</ref>. In imaging, it is desired to suppress the side-lobes of the imaging beam by [[apodization]] techniques. In the case of transmission imaging systems with Gaussian beam distribution, the PSF is modeled by the following equation:<ref>{{Cite journal\|last=Ahi\|first=K.\|date=November 2017\|title=Mathematical Modeling of THz Point Spread Function and Simulation of THz Imaging Systems\|journal=IEEE Transactions on Terahertz Science and Technology\|volume=7\|issue=6\|pages=747–754\|doi=10.1109/tthz.2017.2750690\|issn=2156-342X\|bibcode=2017ITTST...7..747A\|s2cid=11781848}}</ref>		Due to intrinsic limited resolution of the imaging systems, measured PSFs are not free of uncertainty.<ref>{{Cite journal\|last1=Ahi\|first1=Kiarash\|last2=Shahbazmohamadi\|first2=Sina\|last3=Asadizanjani\|first3=Navid\|date=July 2017 \|title=Quality control and authentication of packaged integrated circuits using enhanced-spatial-resolution terahertz time-domain spectroscopy and imaging\|url=https://www.researchgate.net/publication/318712771\|journal=Optics and Lasers in Engineering\|volume=104\|pages=274–284\|doi=10.1016/j.optlaseng.2017.07.007\|bibcode=2018OptLE.104..274A}}</ref> In imaging, it is desired to suppress the side-lobes of the imaging beam by [[apodization]] techniques. In the case of transmission imaging systems with Gaussian beam distribution, the PSF is modeled by the following equation:<ref>{{Cite journal\|last=Ahi\|first=K.\|date=November 2017\|title=Mathematical Modeling of THz Point Spread Function and Simulation of THz Imaging Systems\|journal=IEEE Transactions on Terahertz Science and Technology\|volume=7\|issue=6\|pages=747–754\|doi=10.1109/tthz.2017.2750690\|issn=2156-342X\|bibcode=2017ITTST...7..747A\|s2cid=11781848}}</ref>

	:<math>\mathrm{PSF}(f, z) = I_r(0,z,f)\exp\left[-z\alpha(f)-\dfrac{2\rho^2}{0.36{\frac{cka}{\text{NA}f}}\sqrt{{1+\left ( \frac{2\ln 2}{c\pi}\left ( \frac{\text{NA}}{0.56k} \right )^2 fz\right )}^2}}\right],</math>		:<math>\mathrm{PSF}(f, z) = I_r(0,z,f)\exp\left[-z\alpha(f)-\dfrac{2\rho^2}{0.36{\frac{cka}{\text{NA}f}}\sqrt{{1+\left ( \frac{2\ln 2}{c\pi}\left ( \frac{\text{NA}}{0.56k} \right )^2 fz\right )}^2}}\right],</math>
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	=== Ophthalmology ===		=== Ophthalmology ===

	Point spread functions have recently become a useful diagnostic tool in clinical [[ophthalmology]]. Patients are measured with a [[Shack–Hartmann wavefront sensor\|Shack-Hartmann]] [[wavefront sensor]], and special software calculates the PSF for that patient's eye. This method allows a physician to simulate potential treatments on a patient, and estimate how those treatments would alter the patient's PSF. Additionally, once measured the PSF can be minimized using an adaptive optics system. This, in conjunction with a [[Charge-coupled device\|CCD]] camera and an adaptive optics system, can be used to visualize anatomical structures not otherwise visible ''in vivo'', such as cone photoreceptors <ref>{{Cite journal\|last1=Roorda\|first1=Austin\|last2=Romero-Borja\|first2=Fernando\|last3=Iii\|first3=William J. Donnelly\|last4=Queener\|first4=Hope\|last5=Hebert\|first5=Thomas J.\|last6=Campbell\|first6=Melanie C. W. \|author6-link=Melanie Campbell\|date=2002-05-06\|title=Adaptive optics scanning laser ophthalmoscopy\|journal=Optics Express\|language=EN\|volume=10\|issue=9\|pages=405–412\|doi=10.1364/OE.10.000405\|issn=1094-4087\| bibcode=2002OExpr..10..405R \|pmid=19436374\|s2cid=21971504\|doi-access=free}}</ref>.		Point spread functions have recently become a useful diagnostic tool in clinical [[ophthalmology]]. Patients are measured with a [[Shack–Hartmann wavefront sensor\|Shack-Hartmann]] [[wavefront sensor]], and special software calculates the PSF for that patient's eye. This method allows a physician to simulate potential treatments on a patient, and estimate how those treatments would alter the patient's PSF. Additionally, once measured the PSF can be minimized using an adaptive optics system. This, in conjunction with a [[Charge-coupled device\|CCD]] camera and an adaptive optics system, can be used to visualize anatomical structures not otherwise visible ''in vivo'', such as cone photoreceptors.<ref>{{Cite journal\|last1=Roorda\|first1=Austin\|last2=Romero-Borja\|first2=Fernando\|last3=Iii\|first3=William J. Donnelly\|last4=Queener\|first4=Hope\|last5=Hebert\|first5=Thomas J.\|last6=Campbell\|first6=Melanie C. W. \|author6-link=Melanie Campbell\|date=2002-05-06\|title=Adaptive optics scanning laser ophthalmoscopy\|journal=Optics Express\|language=EN\|volume=10\|issue=9\|pages=405–412\|doi=10.1364/OE.10.000405\|issn=1094-4087\| bibcode=2002OExpr..10..405R \|pmid=19436374\|s2cid=21971504\|doi-access=free}}</ref>

	==See also==		==See also==

Nipun shantha: Moved the dot after the ciation.

2025-04-01T11:55:21Z

Moved the dot after the ciation.

← Previous revision		Revision as of 11:55, 1 April 2025
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	the image of an object in a microscope or telescope as a non-coherent imaging system can be computed by expressing the object-plane field as a weighted sum of 2D impulse functions, and then expressing the image plane field as a weighted sum of the ''images'' of these impulse functions. This is known as the ''superposition principle'', valid for [[linear systems]]. The images of the individual object-plane impulse functions are called point spread functions (PSF), reflecting the fact that a mathematical ''point'' of light in the object plane is ''spread'' out to form a finite area in the image plane. (In some branches of mathematics and physics, these might be referred to as [[Green's functions]] or [[impulse response]] functions. PSFs are considered impulse response functions for imaging systems.		the image of an object in a microscope or telescope as a non-coherent imaging system can be computed by expressing the object-plane field as a weighted sum of 2D impulse functions, and then expressing the image plane field as a weighted sum of the ''images'' of these impulse functions. This is known as the ''superposition principle'', valid for [[linear systems]]. The images of the individual object-plane impulse functions are called point spread functions (PSF), reflecting the fact that a mathematical ''point'' of light in the object plane is ''spread'' out to form a finite area in the image plane. (In some branches of mathematics and physics, these might be referred to as [[Green's functions]] or [[impulse response]] functions. PSFs are considered impulse response functions for imaging systems.
	[[File:PSF Deconvolution V.png\|thumb\|265x265px\|Application of PSF: Deconvolution of the mathematically modeled PSF and the low-resolution image enhances the resolution.<ref name=Kiarash1>{{Cite journal \|last1=Ahi \|first1=Kiarash \|first2=Mehdi \|last2=Anwar \|editor3-first=Tariq \|editor3-last=Manzur \|editor2-first=Thomas W \|editor2-last=Crowe \|editor1-first=Mehdi F \|editor1-last=Anwar \|date=May 26, 2016 \|title=Developing terahertz imaging equation and enhancement of the resolution of terahertz images using deconvolution \|url=https://www.researchgate.net/publication/303563271 \|journal=Proc. SPIE 9856, Terahertz Physics, Devices, and Systems X: Advanced Applications in Industry and Defense, 98560N \|volume=9856 \|pages=98560N \|doi=10.1117/12.2228680\|series=Terahertz Physics, Devices, and Systems X: Advanced Applications in Industry and Defense \|bibcode=2016SPIE.9856E..0NA \|s2cid=114994724 }}</ref>]]		[[File:PSF Deconvolution V.png\|thumb\|265x265px\|Application of PSF: Deconvolution of the mathematically modeled PSF and the low-resolution image enhances the resolution.<ref name=Kiarash1>{{Cite journal \|last1=Ahi \|first1=Kiarash \|first2=Mehdi \|last2=Anwar \|editor3-first=Tariq \|editor3-last=Manzur \|editor2-first=Thomas W \|editor2-last=Crowe \|editor1-first=Mehdi F \|editor1-last=Anwar \|date=May 26, 2016 \|title=Developing terahertz imaging equation and enhancement of the resolution of terahertz images using deconvolution \|url=https://www.researchgate.net/publication/303563271 \|journal=Proc. SPIE 9856, Terahertz Physics, Devices, and Systems X: Advanced Applications in Industry and Defense, 98560N \|volume=9856 \|pages=98560N \|doi=10.1117/12.2228680\|series=Terahertz Physics, Devices, and Systems X: Advanced Applications in Industry and Defense \|bibcode=2016SPIE.9856E..0NA \|s2cid=114994724 }}</ref>]]
	When the object is divided into discrete point objects of varying intensity, the image is computed as a sum of the PSF of each point. As the PSF is typically determined entirely by the imaging system (that is, microscope or telescope), the entire image can be described by knowing the optical properties of the system. This imaging process is usually formulated by a [[convolution]] equation. In [[microscope image processing]] and [[astronomy]], knowing the PSF of the measuring device is very important for restoring the (original) object with [[deconvolution]]. For the case of laser beams, the PSF can be mathematically modeled using the concepts of [[Gaussian beam]]s.<ref name=Kiarash2>{{Cite journal \|last1=Ahi \|first1=Kiarash \|first2=Mehdi \|last2=Anwar \|editor3-first=Tariq \|editor3-last=Manzur \|editor2-first=Thomas W \|editor2-last=Crowe \|editor1-first=Mehdi F \|editor1-last=Anwar \|date=May 26, 2016 \|title=Modeling of terahertz images based on x-ray images: a novel approach for verification of terahertz images and identification of objects with fine details beyond terahertz resolution \|url=https://www.researchgate.net/publication/303563365 \|journal=Proc. SPIE 9856, Terahertz Physics, Devices, and Systems X: Advanced Applications in Industry and Defense, 98560N \|volume=9856 \|page=985610 \|doi=10.1117/12.2228685\|series=Terahertz Physics, Devices, and Systems X: Advanced Applications in Industry and Defense \|bibcode=2016SPIE.9856E..10A \|s2cid=124315172 }}</ref> For instance, deconvolution of the mathematically modeled PSF and the image, improves visibility of features and removes imaging noise.<ref name=Kiarash1/>		When the object is divided into discrete point objects of varying intensity, the image is computed as a sum of the PSF of each point. As the PSF is typically determined entirely by the imaging system (that is, microscope or telescope), the entire image can be described by knowing the optical properties of the system. This imaging process is usually formulated by a [[convolution]] equation. In [[microscope image processing]] and [[astronomy]], knowing the PSF of the measuring device is very important for restoring the (original) object with [[deconvolution]]. For the case of laser beams, the PSF can be mathematically modeled using the concepts of [[Gaussian beam]]s <ref name="Kiarash2">{{Cite journal \|last1=Ahi \|first1=Kiarash \|first2=Mehdi \|last2=Anwar \|editor3-first=Tariq \|editor3-last=Manzur \|editor2-first=Thomas W \|editor2-last=Crowe \|editor1-first=Mehdi F \|editor1-last=Anwar \|date=May 26, 2016 \|title=Modeling of terahertz images based on x-ray images: a novel approach for verification of terahertz images and identification of objects with fine details beyond terahertz resolution \|url=https://www.researchgate.net/publication/303563365 \|journal=Proc. SPIE 9856, Terahertz Physics, Devices, and Systems X: Advanced Applications in Industry and Defense, 98560N \|volume=9856 \|page=985610 \|doi=10.1117/12.2228685\|series=Terahertz Physics, Devices, and Systems X: Advanced Applications in Industry and Defense \|bibcode=2016SPIE.9856E..10A \|s2cid=124315172 }}</ref>. For instance, deconvolution of the mathematically modeled PSF and the image, improves visibility of features and removes imaging noise <ref name="Kiarash1" />.

	==Theory==		==Theory==
Line 58:		Line 58:
	The figure above illustrates the truncation of the incident spherical wave by the lens. In order to measure the point spread function — or impulse response function — of the lens, a perfect point source that radiates a perfect spherical wave in all directions of space is not needed. This is because the lens has only a finite (angular) bandwidth, or finite intercept angle. Therefore, any angular bandwidth contained in the source, which extends past the edge angle of the lens (i.e., lies outside the bandwidth of the system), is essentially wasted source bandwidth because the lens can't intercept it in order to process it. As a result, a perfect point source is not required in order to measure a perfect point spread function. All we need is a light source which has at least as much angular bandwidth as the lens being tested (and of course, is uniform over that angular sector). In other words, we only require a point source which is produced by a convergent (uniform) spherical wave whose half angle is greater than the edge angle of the lens.		The figure above illustrates the truncation of the incident spherical wave by the lens. In order to measure the point spread function — or impulse response function — of the lens, a perfect point source that radiates a perfect spherical wave in all directions of space is not needed. This is because the lens has only a finite (angular) bandwidth, or finite intercept angle. Therefore, any angular bandwidth contained in the source, which extends past the edge angle of the lens (i.e., lies outside the bandwidth of the system), is essentially wasted source bandwidth because the lens can't intercept it in order to process it. As a result, a perfect point source is not required in order to measure a perfect point spread function. All we need is a light source which has at least as much angular bandwidth as the lens being tested (and of course, is uniform over that angular sector). In other words, we only require a point source which is produced by a convergent (uniform) spherical wave whose half angle is greater than the edge angle of the lens.

	Due to intrinsic limited resolution of the imaging systems, measured PSFs are not free of uncertainty.<ref>{{Cite journal\|last1=Ahi\|first1=Kiarash\|last2=Shahbazmohamadi\|first2=Sina\|last3=Asadizanjani\|first3=Navid\|date=July 2017 \|title=Quality control and authentication of packaged integrated circuits using enhanced-spatial-resolution terahertz time-domain spectroscopy and imaging\|url=https://www.researchgate.net/publication/318712771\|journal=Optics and Lasers in Engineering\|volume=104\|pages=274–284\|doi=10.1016/j.optlaseng.2017.07.007\|bibcode=2018OptLE.104..274A}}</ref> In imaging, it is desired to suppress the side-lobes of the imaging beam by [[apodization]] techniques. In the case of transmission imaging systems with Gaussian beam distribution, the PSF is modeled by the following equation:<ref>{{Cite journal\|last=Ahi\|first=K.\|date=November 2017\|title=Mathematical Modeling of THz Point Spread Function and Simulation of THz Imaging Systems\|journal=IEEE Transactions on Terahertz Science and Technology\|volume=7\|issue=6\|pages=747–754\|doi=10.1109/tthz.2017.2750690\|issn=2156-342X\|bibcode=2017ITTST...7..747A\|s2cid=11781848}}</ref>		Due to intrinsic limited resolution of the imaging systems, measured PSFs are not free of uncertainty <ref>{{Cite journal\|last1=Ahi\|first1=Kiarash\|last2=Shahbazmohamadi\|first2=Sina\|last3=Asadizanjani\|first3=Navid\|date=July 2017 \|title=Quality control and authentication of packaged integrated circuits using enhanced-spatial-resolution terahertz time-domain spectroscopy and imaging\|url=https://www.researchgate.net/publication/318712771\|journal=Optics and Lasers in Engineering\|volume=104\|pages=274–284\|doi=10.1016/j.optlaseng.2017.07.007\|bibcode=2018OptLE.104..274A}}</ref>. In imaging, it is desired to suppress the side-lobes of the imaging beam by [[apodization]] techniques. In the case of transmission imaging systems with Gaussian beam distribution, the PSF is modeled by the following equation:<ref>{{Cite journal\|last=Ahi\|first=K.\|date=November 2017\|title=Mathematical Modeling of THz Point Spread Function and Simulation of THz Imaging Systems\|journal=IEEE Transactions on Terahertz Science and Technology\|volume=7\|issue=6\|pages=747–754\|doi=10.1109/tthz.2017.2750690\|issn=2156-342X\|bibcode=2017ITTST...7..747A\|s2cid=11781848}}</ref>

	:<math>\mathrm{PSF}(f, z) = I_r(0,z,f)\exp\left[-z\alpha(f)-\dfrac{2\rho^2}{0.36{\frac{cka}{\text{NA}f}}\sqrt{{1+\left ( \frac{2\ln 2}{c\pi}\left ( \frac{\text{NA}}{0.56k} \right )^2 fz\right )}^2}}\right],</math>		:<math>\mathrm{PSF}(f, z) = I_r(0,z,f)\exp\left[-z\alpha(f)-\dfrac{2\rho^2}{0.36{\frac{cka}{\text{NA}f}}\sqrt{{1+\left ( \frac{2\ln 2}{c\pi}\left ( \frac{\text{NA}}{0.56k} \right )^2 fz\right )}^2}}\right],</math>
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	=== Ophthalmology ===		=== Ophthalmology ===

	Point spread functions have recently become a useful diagnostic tool in clinical [[ophthalmology]]. Patients are measured with a [[Shack–Hartmann wavefront sensor\|Shack-Hartmann]] [[wavefront sensor]], and special software calculates the PSF for that patient's eye. This method allows a physician to simulate potential treatments on a patient, and estimate how those treatments would alter the patient's PSF. Additionally, once measured the PSF can be minimized using an adaptive optics system. This, in conjunction with a [[Charge-coupled device\|CCD]] camera and an adaptive optics system, can be used to visualize anatomical structures not otherwise visible ''in vivo'', such as cone photoreceptors.<ref>{{Cite journal\|last1=Roorda\|first1=Austin\|last2=Romero-Borja\|first2=Fernando\|last3=Iii\|first3=William J. Donnelly\|last4=Queener\|first4=Hope\|last5=Hebert\|first5=Thomas J.\|last6=Campbell\|first6=Melanie C. W. \|author6-link=Melanie Campbell\|date=2002-05-06\|title=Adaptive optics scanning laser ophthalmoscopy\|journal=Optics Express\|language=EN\|volume=10\|issue=9\|pages=405–412\|doi=10.1364/OE.10.000405\|issn=1094-4087\| bibcode=2002OExpr..10..405R \|pmid=19436374\|s2cid=21971504\|doi-access=free}}</ref>		Point spread functions have recently become a useful diagnostic tool in clinical [[ophthalmology]]. Patients are measured with a [[Shack–Hartmann wavefront sensor\|Shack-Hartmann]] [[wavefront sensor]], and special software calculates the PSF for that patient's eye. This method allows a physician to simulate potential treatments on a patient, and estimate how those treatments would alter the patient's PSF. Additionally, once measured the PSF can be minimized using an adaptive optics system. This, in conjunction with a [[Charge-coupled device\|CCD]] camera and an adaptive optics system, can be used to visualize anatomical structures not otherwise visible ''in vivo'', such as cone photoreceptors <ref>{{Cite journal\|last1=Roorda\|first1=Austin\|last2=Romero-Borja\|first2=Fernando\|last3=Iii\|first3=William J. Donnelly\|last4=Queener\|first4=Hope\|last5=Hebert\|first5=Thomas J.\|last6=Campbell\|first6=Melanie C. W. \|author6-link=Melanie Campbell\|date=2002-05-06\|title=Adaptive optics scanning laser ophthalmoscopy\|journal=Optics Express\|language=EN\|volume=10\|issue=9\|pages=405–412\|doi=10.1364/OE.10.000405\|issn=1094-4087\| bibcode=2002OExpr..10..405R \|pmid=19436374\|s2cid=21971504\|doi-access=free}}</ref>.

	==See also==		==See also==

VistaSegoe: /* growthexperiments-addlink-summary-summary:3|0|0 */

2025-03-17T01:36:16Z

Link suggestions feature: 3 links added.

← Previous revision		Revision as of 01:36, 17 March 2025
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	[[Image:SquarePost.svg\|Square Post Function\|right\|thumb\|220px]]		[[Image:SquarePost.svg\|Square Post Function\|right\|thumb\|220px]]

	We imagine the object plane as being decomposed into square areas such as this, with each having its own associated square post function. If the height, ''h'', of the post is maintained at 1/w<sup>2</sup>, then as the side dimension ''w'' tends to zero, the height, ''h'', tends to infinity in such a way that the volume (integral) remains constant at 1. This gives the 2D impulse the shifting property (which is implied in the equation above), which says that when the 2D impulse function, δ(''x'' − ''u'',''y'' − ''v''), is integrated against any other continuous function, {{nowrap\|''f''(''u'',''v'')}}, it "sifts out" the value of ''f'' at the location of the impulse, i.e., at the point {{nowrap\|(''x'',''y'')}}.		We imagine the object plane as being decomposed into square areas such as this, with each having its own associated square post function. If the height, ''h'', of the post is maintained at 1/w<sup>2</sup>, then as the side dimension ''w'' tends to zero, the height, ''h'', tends to infinity in such a way that the volume (integral) remains constant at 1. This gives the 2D impulse the shifting property (which is implied in the equation above), which says that when the 2D impulse function, δ(''x'' − ''u'',''y'' − ''v''), is integrated against any other [[continuous function]], {{nowrap\|''f''(''u'',''v'')}}, it "sifts out" the value of ''f'' at the location of the impulse, i.e., at the point {{nowrap\|(''x'',''y'')}}.

	The concept of a perfect point source object is central to the idea of PSF. However, there is no such thing in nature as a perfect mathematical point source radiator; the concept is completely non-physical and is rather a mathematical construct used to model and understand optical imaging systems. The utility of the point source concept comes from the fact that a point source in the 2D object plane can only radiate a perfect uniform-amplitude, spherical wave — a wave having perfectly spherical, outward travelling phase fronts with uniform intensity everywhere on the spheres (see [[Huygens–Fresnel principle]]). Such a source of uniform spherical waves is shown in the figure below. We also note that a perfect point source radiator will not only radiate a uniform spectrum of propagating plane waves, but a uniform spectrum of exponentially decaying ([[Evanescent wave\|evanescent]]) waves as well, and it is these which are responsible for resolution finer than one wavelength (see [[Fourier optics]]). This follows from the following [[Fourier transform]] expression for a 2D impulse function,		The concept of a perfect point source object is central to the idea of PSF. However, there is no such thing in nature as a perfect mathematical point source radiator; the concept is completely non-physical and is rather a mathematical construct used to model and understand optical imaging systems. The utility of the point source concept comes from the fact that a point source in the 2D object plane can only radiate a perfect uniform-amplitude, spherical wave — a wave having perfectly spherical, outward travelling phase fronts with uniform intensity everywhere on the spheres (see [[Huygens–Fresnel principle]]). Such a source of uniform spherical waves is shown in the figure below. We also note that a perfect point source radiator will not only radiate a uniform spectrum of propagating plane waves, but a uniform spectrum of exponentially decaying ([[Evanescent wave\|evanescent]]) waves as well, and it is these which are responsible for resolution finer than one wavelength (see [[Fourier optics]]). This follows from the following [[Fourier transform]] expression for a 2D impulse function,
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	:<math>\mathrm{PSF}(f, z) = I_r(0,z,f)\exp\left[-z\alpha(f)-\dfrac{2\rho^2}{0.36{\frac{cka}{\text{NA}f}}\sqrt{{1+\left ( \frac{2\ln 2}{c\pi}\left ( \frac{\text{NA}}{0.56k} \right )^2 fz\right )}^2}}\right],</math>		:<math>\mathrm{PSF}(f, z) = I_r(0,z,f)\exp\left[-z\alpha(f)-\dfrac{2\rho^2}{0.36{\frac{cka}{\text{NA}f}}\sqrt{{1+\left ( \frac{2\ln 2}{c\pi}\left ( \frac{\text{NA}}{0.56k} \right )^2 fz\right )}^2}}\right],</math>

	where ''k-factor'' depends on the truncation ratio and level of the irradiance, ''NA'' is numerical aperture, ''c'' is the speed of light, ''f'' is the photon frequency of the imaging beam, ''I<sub>r</sub>'' is the intensity of reference beam, ''a'' is an adjustment factor and <math>\rho</math> is the radial position from the center of the beam on the corresponding ''z-plane''.		where ''k-factor'' depends on the truncation ratio and level of the [[irradiance]], ''NA'' is numerical aperture, ''c'' is the [[speed of light]], ''f'' is the photon frequency of the imaging beam, ''I<sub>r</sub>'' is the intensity of reference beam, ''a'' is an adjustment factor and <math>\rho</math> is the radial position from the center of the beam on the corresponding ''z-plane''.

	==History and methods==		==History and methods==

Hugh Hudson at 21:13, 14 November 2024

2024-11-14T21:13:39Z

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	[[Image:spherical-aberration-disk.jpg\|thumb\|269x269px\|A [[point source]] as imaged by a system with negative (top), zero (center), and positive (bottom) [[spherical aberration]]. Images to the left are [[defocus]]ed toward the inside, images on the right toward the outside.]]		[[Image:spherical-aberration-disk.jpg\|thumb\|269x269px\|A [[point source]] as imaged by a system with negative (top), zero (center), and positive (bottom) [[spherical aberration]]. Images to the left are [[defocus]]ed toward the inside, images on the right toward the outside.]]

	The '''point spread function''' ('''PSF''') describes the response of a focused optical imaging system to a [[point source]] or point object. A more general term for the PSF is the system's [[impulse response]]; the PSF is the impulse response or impulse response function (IRF) of a focused optical imaging system. The PSF in many contexts can be thought of as the ~~extended~~ blob in an image that ~~represents~~ a single point object, ~~that~~ is ~~considered~~ as a spatial impulse. In functional terms, it is the spatial domain version (i.e., the inverse Fourier transform) of the [[Optical transfer function\|optical transfer function (OTF) of an imaging system]]. It is a useful concept in [[Fourier optics]], [[astronomy\|astronomical imaging]], [[medical imaging]], [[electron microscope\|electron microscopy]] and other imaging techniques such as [[dimension\|3D]] [[microscopy]] (like in [[confocal laser scanning microscopy]]) and [[fluorescence microscopy]].		The '''point spread function''' ('''PSF''') describes the response of a focused optical imaging system to a [[point source]] or point object. A more general term for the PSF is the system's [[impulse response]]; the PSF is the impulse response or impulse response function (IRF) of a focused optical imaging system.
			The PSF in many contexts can be thought of as the shapeless blob in an image that should represent a single point object.
			We can consider this as a spatial [[impulse response function]].
			In functional terms, it is the spatial domain version (i.e., the inverse Fourier transform) of the [[Optical transfer function\|optical transfer function (OTF) of an imaging system]]. It is a useful concept in [[Fourier optics]], [[astronomy\|astronomical imaging]], [[medical imaging]], [[electron microscope\|electron microscopy]] and other imaging techniques such as [[dimension\|3D]] [[microscopy]] (like in [[confocal laser scanning microscopy]]) and [[fluorescence microscopy]].

	The degree of spreading (blurring) in the image of a point object for an imaging system is a measure of the quality of the imaging system. In [[non-coherent imaging]] systems, such as [[fluorescent]] [[microscopes]], [[telescopes]] or optical microscopes, the image formation process is linear in the image intensity and described by a [[linear system]] theory. This means that when two objects A and B are imaged simultaneously by a non-coherent imaging system, the resulting image is equal to the sum of the independently imaged objects. In other words: the imaging of A is unaffected by the imaging of B and ''vice versa'', owing to the non-interacting property of photons. In space-invariant systems, i.e. those in which the PSF is the same everywhere in the imaging space, the image of a complex object is then the [[convolution]] of that object and the PSF. The PSF can be derived from diffraction integrals.<ref>{{Cite book\|url=https://books.google.com/books?id=lCm9Q18P8cMC&q=diffraction+integral+point+spread+function&pg=PA355\|title=Progress in Optics\|date=2008-01-25\|publisher=Elsevier\|isbn=978-0-08-055768-7\|language=en\|page=355}}</ref>		The degree of spreading (blurring) in the image of a point object for an imaging system is a measure of the quality of the imaging system. In [[non-coherent imaging]] systems, such as [[fluorescent]] [[microscopes]], [[telescopes]] or optical microscopes, the image formation process is linear in the image intensity and described by a [[linear system]] theory. This means that when two objects A and B are imaged simultaneously by a non-coherent imaging system, the resulting image is equal to the sum of the independently imaged objects. In other words: the imaging of A is unaffected by the imaging of B and ''vice versa'', owing to the non-interacting property of photons. In space-invariant systems, i.e. those in which the PSF is the same everywhere in the imaging space, the image of a complex object is then the [[convolution]] of that object and the PSF. The PSF can be derived from diffraction integrals.<ref>{{Cite book\|url=https://books.google.com/books?id=lCm9Q18P8cMC&q=diffraction+integral+point+spread+function&pg=PA355\|title=Progress in Optics\|date=2008-01-25\|publisher=Elsevier\|isbn=978-0-08-055768-7\|language=en\|page=355}}</ref>

134.171.70.47: /* Theory */ spelling improved

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Theory: spelling improved

← Previous revision		Revision as of 14:04, 25 June 2024
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	[[Image:SquarePost.svg\|Square Post Function\|right\|thumb\|220px]]		[[Image:SquarePost.svg\|Square Post Function\|right\|thumb\|220px]]

	We imagine the object plane as being decomposed into square areas such as this, with each having its own associated square post function. If the height, ''h'', of the post is maintained at 1/w<sup>2</sup>, then as the side dimension ''w'' tends to zero, the height, ''h'', tends to infinity in such a way that the volume (integral) remains constant at 1. This gives the 2D impulse the ~~sifting~~ property (which is implied in the equation above), which says that when the 2D impulse function, δ(''x'' − ''u'',''y'' − ''v''), is integrated against any other continuous function, {{nowrap\|''f''(''u'',''v'')}}, it "sifts out" the value of ''f'' at the location of the impulse, i.e., at the point {{nowrap\|(''x'',''y'')}}.		We imagine the object plane as being decomposed into square areas such as this, with each having its own associated square post function. If the height, ''h'', of the post is maintained at 1/w<sup>2</sup>, then as the side dimension ''w'' tends to zero, the height, ''h'', tends to infinity in such a way that the volume (integral) remains constant at 1. This gives the 2D impulse the shifting property (which is implied in the equation above), which says that when the 2D impulse function, δ(''x'' − ''u'',''y'' − ''v''), is integrated against any other continuous function, {{nowrap\|''f''(''u'',''v'')}}, it "sifts out" the value of ''f'' at the location of the impulse, i.e., at the point {{nowrap\|(''x'',''y'')}}.

	The concept of a perfect point source object is central to the idea of PSF. However, there is no such thing in nature as a perfect mathematical point source radiator; the concept is completely non-physical and is rather a mathematical construct used to model and understand optical imaging systems. The utility of the point source concept comes from the fact that a point source in the 2D object plane can only radiate a perfect uniform-amplitude, spherical wave — a wave having perfectly spherical, outward travelling phase fronts with uniform intensity everywhere on the spheres (see [[Huygens–Fresnel principle]]). Such a source of uniform spherical waves is shown in the figure below. We also note that a perfect point source radiator will not only radiate a uniform spectrum of propagating plane waves, but a uniform spectrum of exponentially decaying ([[Evanescent wave\|evanescent]]) waves as well, and it is these which are responsible for resolution finer than one wavelength (see [[Fourier optics]]). This follows from the following [[Fourier transform]] expression for a 2D impulse function,		The concept of a perfect point source object is central to the idea of PSF. However, there is no such thing in nature as a perfect mathematical point source radiator; the concept is completely non-physical and is rather a mathematical construct used to model and understand optical imaging systems. The utility of the point source concept comes from the fact that a point source in the 2D object plane can only radiate a perfect uniform-amplitude, spherical wave — a wave having perfectly spherical, outward travelling phase fronts with uniform intensity everywhere on the spheres (see [[Huygens–Fresnel principle]]). Such a source of uniform spherical waves is shown in the figure below. We also note that a perfect point source radiator will not only radiate a uniform spectrum of propagating plane waves, but a uniform spectrum of exponentially decaying ([[Evanescent wave\|evanescent]]) waves as well, and it is these which are responsible for resolution finer than one wavelength (see [[Fourier optics]]). This follows from the following [[Fourier transform]] expression for a 2D impulse function,

134.171.70.47: /* Theory */

2024-06-25T14:00:26Z

Theory

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	:<math> O(x_o,y_o) = \iint O(u,v) ~ \delta(x_o-u,y_o-v) ~ du\, dv</math>		:<math> O(x_o,y_o) = \iint O(u,v) ~ \delta(x_o-u,y_o-v) ~ du\, dv</math>

	i.e., as a sum over weighted impulse functions, although this is also really just stating the ~~sifting~~ property of 2D delta functions (discussed further below). Rewriting the object transmittance function in the form above allows us to calculate the image plane field as the superposition of the images of each of the individual impulse functions, i.e., as a superposition over weighted point spread functions in the image plane using the ''same'' weighting function as in the object plane, i.e., <math>O(x_o,y_o)</math>. Mathematically, the image is expressed as:		i.e., as a sum over weighted impulse functions, although this is also really just stating the shifting property of 2D delta functions (discussed further below). Rewriting the object transmittance function in the form above allows us to calculate the image plane field as the superposition of the images of each of the individual impulse functions, i.e., as a superposition over weighted point spread functions in the image plane using the ''same'' weighting function as in the object plane, i.e., <math>O(x_o,y_o)</math>. Mathematically, the image is expressed as:

	:<math>I(x_i,y_i) = \iint O(u,v) ~ \mathrm{PSF}(x_i/M-u , y_i/M-v) \, du\, dv</math>		:<math>I(x_i,y_i) = \iint O(u,v) ~ \mathrm{PSF}(x_i/M-u , y_i/M-v) \, du\, dv</math>

Me, Myself, and I are Here: /* See also */alpha

2023-12-06T04:45:17Z

Me, Myself, and I are Here: /* See also */alpha

2023-12-05T00:12:14Z

AnomieBOT: Substing templates: {{Format ISBN}}. See User:AnomieBOT/docs/TemplateSubster for info.

2023-09-28T13:22:47Z

Substing templates: {{Format ISBN}}. See User:AnomieBOT/docs/TemplateSubster for info.

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	\| publisher = Academic Press		\| publisher = Academic Press
	\| year = 2006		\| year = 2006
	\| isbn = ~~{{Format ISBN\|9780121828196}}~~		\| isbn = 978-0-12-182819-6
	\| pages = [https://archive.org/details/methodsinenzymol414ingl/page/223 223–224]		\| pages = [https://archive.org/details/methodsinenzymol414ingl/page/223 223–224]
	\| chapter-url = https://books.google.com/books?id=5bczPeokiqAC&pg=PA223		\| chapter-url = https://books.google.com/books?id=5bczPeokiqAC&pg=PA223

← Previous revision		Revision as of 15:47, 8 May 2025
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	[[Image:SquarePost.svg\|Square Post Function\|right\|thumb\|220px]]		[[Image:SquarePost.svg\|Square Post Function\|right\|thumb\|220px]]

	We imagine the object plane as being decomposed into square areas such as this, with each having its own associated square post function. If the height, ''h'', of the post is maintained at 1/w<sup>2</sup>, then as the side dimension ''w'' tends to zero, the height, ''h'', tends to infinity in such a way that the volume (integral) remains constant at 1. This gives the 2D impulse the ~~shifting~~ property (which is implied in the equation above), which says that when the 2D impulse function, δ(''x'' − ''u'',''y'' − ''v''), is integrated against any other [[continuous function]], {{nowrap\|''f''(''u'',''v'')}}, it "sifts out" the value of ''f'' at the location of the impulse, i.e., at the point {{nowrap\|(''x'',''y'')}}.		We imagine the object plane as being decomposed into square areas such as this, with each having its own associated square post function. If the height, ''h'', of the post is maintained at 1/w<sup>2</sup>, then as the side dimension ''w'' tends to zero, the height, ''h'', tends to infinity in such a way that the volume (integral) remains constant at 1. This gives the 2D impulse the sifting property (which is implied in the equation above), which says that when the 2D impulse function, δ(''x'' − ''u'',''y'' − ''v''), is integrated against any other [[continuous function]], {{nowrap\|''f''(''u'',''v'')}}, it "sifts out" the value of ''f'' at the location of the impulse, i.e., at the point {{nowrap\|(''x'',''y'')}}.

	The concept of a perfect point source object is central to the idea of PSF. However, there is no such thing in nature as a perfect mathematical point source radiator; the concept is completely non-physical and is rather a mathematical construct used to model and understand optical imaging systems. The utility of the point source concept comes from the fact that a point source in the 2D object plane can only radiate a perfect uniform-amplitude, spherical wave — a wave having perfectly spherical, outward travelling phase fronts with uniform intensity everywhere on the spheres (see [[Huygens–Fresnel principle]]). Such a source of uniform spherical waves is shown in the figure below. We also note that a perfect point source radiator will not only radiate a uniform spectrum of propagating plane waves, but a uniform spectrum of exponentially decaying ([[Evanescent wave\|evanescent]]) waves as well, and it is these which are responsible for resolution finer than one wavelength (see [[Fourier optics]]). This follows from the following [[Fourier transform]] expression for a 2D impulse function,		The concept of a perfect point source object is central to the idea of PSF. However, there is no such thing in nature as a perfect mathematical point source radiator; the concept is completely non-physical and is rather a mathematical construct used to model and understand optical imaging systems. The utility of the point source concept comes from the fact that a point source in the 2D object plane can only radiate a perfect uniform-amplitude, spherical wave — a wave having perfectly spherical, outward travelling phase fronts with uniform intensity everywhere on the spheres (see [[Huygens–Fresnel principle]]). Such a source of uniform spherical waves is shown in the figure below. We also note that a perfect point source radiator will not only radiate a uniform spectrum of propagating plane waves, but a uniform spectrum of exponentially decaying ([[Evanescent wave\|evanescent]]) waves as well, and it is these which are responsible for resolution finer than one wavelength (see [[Fourier optics]]). This follows from the following [[Fourier transform]] expression for a 2D impulse function,

← Previous revision		Revision as of 14:04, 25 June 2024
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	[[Image:SquarePost.svg\|Square Post Function\|right\|thumb\|220px]]		[[Image:SquarePost.svg\|Square Post Function\|right\|thumb\|220px]]

	We imagine the object plane as being decomposed into square areas such as this, with each having its own associated square post function. If the height, ''h'', of the post is maintained at 1/w<sup>2</sup>, then as the side dimension ''w'' tends to zero, the height, ''h'', tends to infinity in such a way that the volume (integral) remains constant at 1. This gives the 2D impulse the ~~sifting~~ property (which is implied in the equation above), which says that when the 2D impulse function, δ(''x'' − ''u'',''y'' − ''v''), is integrated against any other continuous function, {{nowrap\|''f''(''u'',''v'')}}, it "sifts out" the value of ''f'' at the location of the impulse, i.e., at the point {{nowrap\|(''x'',''y'')}}.		We imagine the object plane as being decomposed into square areas such as this, with each having its own associated square post function. If the height, ''h'', of the post is maintained at 1/w<sup>2</sup>, then as the side dimension ''w'' tends to zero, the height, ''h'', tends to infinity in such a way that the volume (integral) remains constant at 1. This gives the 2D impulse the shifting property (which is implied in the equation above), which says that when the 2D impulse function, δ(''x'' − ''u'',''y'' − ''v''), is integrated against any other continuous function, {{nowrap\|''f''(''u'',''v'')}}, it "sifts out" the value of ''f'' at the location of the impulse, i.e., at the point {{nowrap\|(''x'',''y'')}}.

	The concept of a perfect point source object is central to the idea of PSF. However, there is no such thing in nature as a perfect mathematical point source radiator; the concept is completely non-physical and is rather a mathematical construct used to model and understand optical imaging systems. The utility of the point source concept comes from the fact that a point source in the 2D object plane can only radiate a perfect uniform-amplitude, spherical wave — a wave having perfectly spherical, outward travelling phase fronts with uniform intensity everywhere on the spheres (see [[Huygens–Fresnel principle]]). Such a source of uniform spherical waves is shown in the figure below. We also note that a perfect point source radiator will not only radiate a uniform spectrum of propagating plane waves, but a uniform spectrum of exponentially decaying ([[Evanescent wave\|evanescent]]) waves as well, and it is these which are responsible for resolution finer than one wavelength (see [[Fourier optics]]). This follows from the following [[Fourier transform]] expression for a 2D impulse function,		The concept of a perfect point source object is central to the idea of PSF. However, there is no such thing in nature as a perfect mathematical point source radiator; the concept is completely non-physical and is rather a mathematical construct used to model and understand optical imaging systems. The utility of the point source concept comes from the fact that a point source in the 2D object plane can only radiate a perfect uniform-amplitude, spherical wave — a wave having perfectly spherical, outward travelling phase fronts with uniform intensity everywhere on the spheres (see [[Huygens–Fresnel principle]]). Such a source of uniform spherical waves is shown in the figure below. We also note that a perfect point source radiator will not only radiate a uniform spectrum of propagating plane waves, but a uniform spectrum of exponentially decaying ([[Evanescent wave\|evanescent]]) waves as well, and it is these which are responsible for resolution finer than one wavelength (see [[Fourier optics]]). This follows from the following [[Fourier transform]] expression for a 2D impulse function,

← Previous revision		Revision as of 04:45, 6 December 2023
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	* [[Circle of confusion]], for the closely related topic in general photography.		* [[Circle of confusion]], for the closely related topic in general photography.
	* [[Deconvolution]]		* [[Deconvolution]]
⚫	* [[Impulse response function]]
	* [[Encircled energy]]		* [[Encircled energy]]
		⚫	* [[Impulse response function]]
	* [[Microscope]]		* [[Microscope]]
	* [[Microsphere]]		* [[Microsphere]]

← Previous revision		Revision as of 00:12, 5 December 2023
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	==See also==		==See also==

⚫	* [[Circle of confusion]], for the closely related topic in general photography.
	* [[Airy disc]]		* [[Airy disc]]
		⚫	* [[Circle of confusion]], for the closely related topic in general photography.
⚫	* [[Encircled energy]]
	* [[PSF Lab]]
	* [[Deconvolution]]		* [[Deconvolution]]
			* [[Impulse response function]]
		⚫	* [[Encircled energy]]
	* [[Microscope]]		* [[Microscope]]
	* [[Microsphere]]		* [[Microsphere]]
	* [[~~Impulse~~ ~~response function~~]]		* [[PSF Lab]]

	==References==		==References==