Adaptive four windows wavelet image denoising based on local polynomial approximation-intersection of confidence intervals

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.