A multilevel regression-analysis-based nonlocal means denoising algorithm A multilevel regression-analysis-based nonlocal means denoising algorithm A multilevel regression-analysis-based nonlocal means denoising algorithm

摘要

This paper focuses on image denoising under the powerful framework-non local means. First, the introduction and development of NL-means is discussed. Second, a powerful scheme based on linear regression analysis for the classification of image meaningful parts is proposed. Third, an improved version of NL-means is carried out, which uses a novel patch similarity rule based on quadratic regression analysis. This multilevel regression analysis based algorithm can better describe and smooth the noisy image and finally, experimental results validate the algorithm in both effectiveness and efficiency.