Point spread function Totally Explained

Everything about The Point Spread Function totally explained

The point spread function (PSF) describes the response of an imaging system to a point source or point object. A related but more general term for the PSF is a system's impulse response. The PSF in many contexts can be thought of as the extended blob in an image that represents an unresolved object. In functional terms it's the spatial domain version of the modulation transfer function. It is a useful concept in Fourier optics, astronomical imaging, electron microscopy and other imaging techniques such as 3D microscopy (like in Confocal laser scanning microscopy) and fluorescence microscopy. The degree of spreading (blurring) of the point object is a measure for the quality of an imaging system. In incoherent imaging systems such as fluorescent microscopes, telescopes or optical microscopes, the image formation process is linear in power and described by linear system theory. When the light is coherent, image formation is linear in complex field. This means that when two objects A and B are imaged simultaneously, the result 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. (The sum is of the light waves which may result in destructive and constructive interference at non-image planes.)

Introduction

By virtue of the linearity property of optical imaging systems, for example, ť Image(Object₁ + Object₂) = Image(Object₁) + Image(Object₂)

the image of an object in a microscope or telescope can be computed by expressing the object-plane field as a weighted sum over 2D impulse functions, and then expressing the image plane field as the weighted sum over 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, 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).
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 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) image with deconvolution.

Theory

The point spread function may be independent of position in the object plane, in which case it's called shift invariant. In addition, if there's no distortion in the system, the image plane coordinates are linearly related to the object plane coordinates via the magnification M as: ť

(x_i, y_i) = (M x_o, M y_o)

.

If the imaging system produces an inverted image, we may simply regard the image plane coordinate axes as being reversed from the object plane axes. With these two assumptions, for example, that the PSF is shift-invariant and that there's no distortion, calculating the image plane convolution integral is a straightforward process.
Mathematically, we may represent the object plane field as:
ť

O(x_o,y_o) = int!!int O(u,v) ~ delta(x_o-u,y_o-v) ~ du, dv

for example, 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, for example, as a superposition over weighted point spread functions in the image plane using the same weighting function as in the object plane, for example,

O(x_o,y_o)

. Mathematically, the image is expressed as:
ť

I(x_i,y_i) = int!!int O(u,v) ~ mathrm , d k_x, d k_y

lens intercepts a portion of this spherical wave (and the key phrase here's a portion), and refocuses it onto a blurred point in the image plane. For a single lens, an on-axis point source in the object plane produces an Airy disc PSF in the image plane. This comes about in the following way. It can be shown (see Fourier optics, Huygens-Fresnel principle, Fraunhofer diffraction) that the field radiated by a planar object (or, by reciprocity, the field converging onto a planar image) is related to its corresponding source (or image) plane distribution via a Fourier transform (FT) relation. In addition, a uniform function over a circular area (in one FT domain) corresponds to the Airy function, J₁(x)/x in the other FT domain, where J₁(x) is the first-order Bessel function of the first kind. That is, a uniformly-illuminated circular aperture radiates an Airy function pattern plus a converging uniform spherical wave (over a circular angular sector) and yields an Airy function image. A graph of a sample 2D Airy function is shown in the adjoining figure (click to enlarge).
Therefore, the converging (partial) spherical wave shown in the figure above produces an Airy disc in the image plane. The argument of the Airy function is important, because this determines the scaling of the Airy disc (in other words, how big the disc is in the image plane). If Θ_max is the maximum angle that the converging waves make with the lens axis, r is radial distance in the image plane, and wavenumber k = 2π/λ where λ = wavelength, then the argument of the Airy function is: kr sin(Θ_max). If Θ_max is small (only a small portion of the converging spherical wave is available to form the image), then radial distance, r, has to be very large before the total argument of the Airy function moves away from the central spot. In other words, if Θ_max is small, the Airy disc is large (which is just another statement of Heisenberg's uncertainty principle for FT pairs, namely that small extent in one domain corresponds to wide extent in the other domain, and the two are related via the space-bandwidth product. By virtue of this, high magnification systems, which typically have small values of Θ_max (by the Abbe sine condition), can have more blur in the image, owing to the broader PSF. The size of the PSF is proportional to the magnification, so that the blur is no worse in a relative sense, but it's definitely worse in an absolute sense.

History and methods

The diffraction theory of point-spread functions was first studied by Airy in the nineteenth century. He developed an expression for the point-spread function amplitude and intensity of a perfect instrument, free of aberrations (the so-called Airy disc). The theory of aberrated point-spread functions close to the optimum focal plane was studied by the Dutch physicists Fritz Zernike and Nijboer in the 1930–40s. A central role in their analysis is played by Zernike’s circle polynomials that allow an efficient representation of the aberrations of any optical system with rotational symmetry. Recent analytic results have made it possible to extend Nijboer and Zernike’s approach for point-spread function evaluation to a large volume around the optimum focal point. This Extended Nijboer-Zernike (ENZ) theory

is instrumental in studying the imperfect imaging of three-dimensional objects in confocal microscopy or astronomy under non-ideal imaging conditions. The ENZ-theory has also been applied to the characterization of optical instruments with respect to their aberration by measuring the through-focus intensity distribution and solving an appropriate inverse problem.

PSF in microscopy

In microscopy, experimental determination of a PSF is usually tricky, due to the difficulty of finding sub-resolution (point-like) radiating sources. Quantum dots and fluorescent beads are usually considered for this purpose.

The PSF in astronomy

In observational astronomy the experimental determination of a PSF is often very straightforward due to the ample supply of point sources (stars or quasars). The form and source of the PSF may vary widely depending on the instrument and the context in which it's used.
For radio telescopes and diffraction-limited space telescopes the dominant terms in the PSF may be inferred from the configuration of the aperture in the Fourier domain. In practice there may be multiple terms contributed by the various components in a complex optical system. A complete description of the PSF will also include diffusion of light (or photo-electrons) in the detector, as well as tracking errors in the spacecraft.
For ground based optical telescopes, atmospheric turbulence (known as astronomical seeing) dominates the contribution to the PSF. In high-resolution ground-based imaging, the PSF is often found to vary with position in the image (an effect called anisoplanatism). In ground based adaptive optics systems the PSF is a combination of the aperture of the system with residual uncorrected atmospheric terms.

Point spread functions in ophthalmology

PSFs have recently become a useful diagnostic tool in clinical ophthalmology. Patients are measured with a wavefront sensor, and special software calculates the PSF for that patient’s eye. In this manner a physician can "see" what the patient sees. This method also allows a physician to simulate potential treatments on a patient, and see 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 CCD, can be used to visualize anatomical structures not otherwise visible in vivo, such as cone photoreceptors.

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