Adaptive window size image denoising based on ICI rule
نویسندگان
چکیده
An algorithm for image noise-removal based on local adaptive window size ¿ltering is developed in this paper. Two features to use into local spatial/transform-domain ¿ltering are suggested. First, ¿ltering is performed on images corrupted not only by additive white noise, but also by imagedependent (e.g. ¿lm-grain noise) or multiplicative noise. Second, used transforms are equipped with a varying adaptive window size obtained by the intersection of con¿dence intervals (ICI) rule. Finally, we combine all estimates available for each pixel from neighboring overlapping windows by weighted averaging these estimates. Comparison of the algorithm with the known techniques for noise removal from images shows the advantage of the new algorithm, both quantitatively and visually.
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