Philip N. H. Nakashima
The Aperture Method for Measuring Point Spread Functions (AMMPSF)
The AMMPSF software is designed to measure accurately a Point Spread Function (PSF) / Modulation Transfer Function (MTF). The AMMPSF software is written in C/C++ and is based on the Digital Micrograph Script described in detail in:
AMMPSF makes use of Nakashima and Johnson's "aperture method" for PSF/MTF measurement [1] and is applicable to any digital imaging system. Only one minor modification to the original algorithm detailed in [1] was made to arrive at the present AMMPSF software. This modification is detailed in:
A comparison of pros and cons of published PSF/MTF measurement techniques
There are numerous advantages to the AMMPSF approach over others that have been presented in the literature (for summaries, see [1] and [2]). The table below illustrates the differences.
Technique | Example | Pros | Cons |
---|---|---|---|
Blind Deconvolution | |||
a) | Richardson-Lucy Algorithm | Richardson-Lucy Algorithm |
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Stochastic Input | |||
a) | The Noise Method | Only requires uniform illumination |
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b) | Amorphous Film Imaging (TEM) | Only requires uniform illumination |
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Deterministic Input | |||
a) | Slit/Line Methods |
|
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b) | The Point Source Method |
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c) | Periodic Intensity Methods (incl. Gratings and Holographic Fringes) |
|
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d) | The Knife-Edge Method |
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e) | The Aperture Method (AMMPSF) |
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How to use AMMPSF
1. Collect a focused image of an aperture
A: Image of an aperture which is not perfectly circular and has some arbitrary geometry.
B: Expanded view of the right edge with an intensity profile locus crossing it (see C).
C: The intensity gradient about the edge is symmetric indicating the image is in focus - see instructions with the download.
2. AMMPSF determines the aperture shape to sub-pixel resolution
A: The "top hat" function representing the idealised intensity through the aperture.
B: Expanded view of the right edge with an intensity profile locus crossing it (see C).
C: Intensity profile showing the step between 0 and maximum intensity at the partially exposed pixel at the edge returned from the sub-pixel shape determination.
3. Deconvolution of the input image with the aperture shape gives the PSF.
The PSF is radially averaged to reduce noise.
A: The peak region of the radially averaged PSF returned after IFFT(FFT(1A)/FFT(2A)).
i.e. deconvolution of the as-captured aperture image in 1A by the aperture shape determined by AMMPSF in 2A returns a PSF which is smoothed by radial averaging. The centre 64x64 pixels from the present example (2048x2048) are shown here. The locus corresponds to B.
B: The intensity profile across the PSF peak along the locus shown in A.
C: A surface plot of the 64x64 pixel region shown in A.