The digital TV filter and nonlinear denoising

Tony F. Chan*, Stanley Osher, Jianhong Shen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

423 Scopus citations


Motivated by the classical TV (total variation) restoration model, we propose a new nonlinear filter - the digital TV filter for denoising and enhancing digital images, or more generally, data living on graphs. The digital TV filter is a data dependent lowpass filter, capable of denoising data without blurring jumps or edges. In iterations, it solves a global total variational (or L 1) optimization problem, which differs from most statistical filters. Applications are given in the denoising of one-dimensional (1-D) signals, two-dimensional (2-D) data with irregular structures, gray scale and color images, and nonflat image features such as chromaticity.

Original languageEnglish (US)
Pages (from-to)231-241
Number of pages11
JournalIEEE Transactions on Image Processing
Issue number2
StatePublished - Dec 1 2001
Externally publishedYes


  • Chromaticity
  • Color images
  • Data-dependent
  • Denoising
  • Digital filters
  • Edge-enhancement
  • Graph
  • Median filters
  • Nonlinear
  • Restoration
  • Total variation (TV)

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design


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