Title: Total variation denoising (an MM algorithm)
Abstract: Total variation denoising (TVD) is an approach for noise reduction developed so as to preserve sharp edges in the underlying signal. Unlike a conventional low-pass lter, TV denoising is de ned in terms of an optimization problem. This module describes an algorithm for TV denoising derived using the majorization-minimization (MM) approach, developed by Figueiredo et al. [ICIP 2006]. To keep it simple, this module addresses TV denoising of 1-D signals only. For computational e ciency, the algorithm may use a solver for sparse banded systems.
Publication Year: 2012
Publication Date: 2012-12-03
Language: en
Type: article
Access and Citation
Cited By Count: 50
AI Researcher Chatbot
Get quick answers to your questions about the article from our AI researcher chatbot