期刊
INTERNATIONAL JOURNAL OF COMPUTER VISION
卷 52, 期 2-3, 页码 189-203出版社
KLUWER ACADEMIC PUBL
DOI: 10.1023/A:1022908225256
关键词
nonlinear diffusion; stopping time; regularization parameter; image restoration; scale space
We develop a novel time-selection strategy for iterative image restoration techniques: the stopping time is chosen so that the correlation of signal and noise in the filtered image is minimized. The new method is applicable to any images where the noise to be removed is uncorrelated with the signal, under the assumptions that the filter used is suitable for the given type of data, and that neither the additive noise nor the filtering procedure alter the average gray value; no other knowledge (e. g. the noise variance, training data etc.) is needed. We analyse the theoretical properties of the method, then test the performance of our time estimation procedure experimentally, and demonstrate that it yields near-optimal results for a wide range of noise levels and for various filtering methods.
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