An algorithm for image noise-removal based on local adaptive window size filtering is developed in this paper. Two features to use into local spatial/transform-domain filtering are suggested. First, filtering is performed on images corrupted not only by additive white noise, but also by image-dependent (e.g. film-grain noise) or multiplicative noise. Second, used transforms are equipped with a varying adaptive window size obtained by the intersection of confidence 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.
CITATION STYLE
Egiazarian, K., Katkovnik, V., & Astola, J. (2001). Adaptive window size image denoising based on ICI rule. In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings (Vol. 3, pp. 1869–1872). Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/icassp.2001.941308
Mendeley helps you to discover research relevant for your work.