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When you use the deconvolution method to make the blurry image sharper, you will have to estimate the Point Spread Function. Is there a difference between this PSF and an image kernel?

Second question: Is the Point Spread Function in the time domain or frequency domain? Or can it be in both?

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  • $\begingroup$ Could you, please, review my answer? If it answers your question, could you mark it? $\endgroup$
    – Royi
    Sep 24, 2022 at 17:17

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There is a slight difference in definition and in context. A PSF does not need to be a convolution kernel, however, it is almost always assumed to be one. Usually, you talk of a ,,PSF'' when you want to find out what it is, exactly, and of a ,,convolution kernel'' when you're aware that there is a convolution.

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  • $\begingroup$ So, they are the same in the context of convolution and deconvolution? $\endgroup$
    – Teede
    Jan 3, 2014 at 11:25
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The PSF (Point Spread Function) is the system response to Impulse Signal (Point).

If your system model is LSI (Linear Spatially Invariant) then the output image of the system is applying the PSF as a convolution kernel on the input image.

Yet, the PSF is just the response of a system to a certain input.
It doesn't describe the whole system unless it is an LSI system.

If you model for the Deconvolution problem (Often called the Degradation Model) is LSI, then what you estimate is indeed the PSF.

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  • $\begingroup$ reading your answer I understand I need to do some more reading. can you recommend me on a reference text to get a deeper understanding of system models etc? $\endgroup$
    – bla
    Jun 23, 2020 at 16:56
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    $\begingroup$ @bla, I think Digital Image Processing by Gonzalez/Woods is a great place to start. Also Richard Szeliski - Computer Vision: Algorithms and Applications is a great and freee resource. If you liked the answer, please +1. $\endgroup$
    – Royi
    Jun 23, 2020 at 19:32

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