全变差去噪
正规化(语言学)
算法
反褶积
忠诚
计算机科学
高斯分布
规范(哲学)
数学
人工智能
降噪
政治学
量子力学
电信
物理
法学
作者
Paul Rodriguez,Brendt Wohlberg
出处
期刊:Asilomar Conference on Signals, Systems and Computers
日期:2006-10-01
被引量:23
标识
DOI:10.1109/acssc.2006.354879
摘要
Total variation (TV) regularization has become a popular method for a wide variety of image restoration problems, including denoising and deconvolution. Recently, a number of authors have noted the advantages, including superior performance with certain non-Gaussian noise, of replacing the standard lscr 2 data fidelity term with an lscr 1 norm. We propose a simple but very flexible and computationally efficient method, the iteratively reweighted norm algorithm, for minimizing a generalized TV functional which includes both the lscr 2 -TV and and lscr2-TV problems.
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