An Adaption of the Lucy-Richardson Deconvolution Algorithm to Noncentral Chi-Square Distributed Data
نویسندگان
چکیده
The Lucy-Richardson Algorithm is a well-known iterative method for the deconvolution of images convolved with a known point spread function. It is derived from a statistical point of view as it converges to the maximum-likelihood solution under the condition that the data follow a Poisson distribution. This assumption holds true for images detected by a digital camera. However, there are images not following a Poisson but rather a noncentral chi-square distribution. Here we show an adaption of the Lucy-Richardson algorithm to be used for data following this probability distribution. Its application to simulated and real data from an imaging radar sensor shows its advantage over the original algorithm.
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