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20 September 2001 Parameter estimation method of space-variant degraded image using the normalized entropy evaluation
Tomokazu Tamaoki, Noboru Funakubo
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Proceedings Volume 4552, Image Matching and Analysis; (2001) https://doi.org/10.1117/12.441506
Event: Multispectral Image Processing and Pattern Recognition, 2001, Wuhan, China
Abstract
In this paper, we discuss a method which performs image restoration from an observed image with space-variant degradation. Here, it is assumed that the degradation parameter is not known, though the type of its degradation function is known beforehand. In this case, to restore image from observed one, we propose some new evaluation functions for estimating the degradation parameter. We defined the image entropy and the Laplacian entropy as these evaluation functions by considering the average value. In addition, the normalized entropy was defined by unifying these two entropies. Because of space-variant degradation the partial evaluation area is small and the degradation parameter changes little by little at each evaluation area. By our method the parameter quantity which gives the maximum evaluation value of the normalized entropy is adopted as the estimated degradation parameter value. In actual application at present, the partial evaluation areas to all pixels of an observed image are sequentially set. And, the image can be restored based on the estimated degradation parameters which are obtained by these evaluation functions respectively. Through the results of some simulation experiments, we have already validated the well-restored images. Also, we have been treating degradation images including impulse noise.
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Tomokazu Tamaoki and Noboru Funakubo "Parameter estimation method of space-variant degraded image using the normalized entropy evaluation", Proc. SPIE 4552, Image Matching and Analysis, (20 September 2001); https://doi.org/10.1117/12.441506
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KEYWORDS
Image restoration
Image analysis
Point spread functions
Image information entropy
Image processing
Interference (communication)
Digital filtering
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