15 November 2007 Adaptive four windows wavelet image denoising based on local polynomial approximation-intersection of confidence intervals
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Proceedings Volume 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition; 67862H (2007) https://doi.org/10.1117/12.749693
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China
Abstract
Local Polynomial Approximation-Intersection of Confidence Intervals (LPA-ICI) is a new approach, which can find the boundary of the isotropic region efficiently, especially for noisy images. This paper presents a novel image denoising method, adaptive four windows wavelet image denoising based on LPA-ICI, which is composed of three parts: searching for four adaptive windows with LPA-ICI, updating the noisy wavelet coefficients by hard threshold and obtaining a final "clean" pixel value by fusing the updated pixels with different weights which are determined by the sparsity of regions. Experiments show that our algorithm has advanced performance, reconstructed edges are clean, and especially without unpleasant ringing artifacts.
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Hongxiao Feng, Hongxiao Feng, Biao Hou, Biao Hou, Licheng Jiao, Licheng Jiao, Haigang Li, Haigang Li, } "Adaptive four windows wavelet image denoising based on local polynomial approximation-intersection of confidence intervals", Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 67862H (15 November 2007); doi: 10.1117/12.749693; https://doi.org/10.1117/12.749693
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