Title :
The digital TV filter and nonlinear denoising
Author :
Chan, Tony F. ; Osher, Stanley ; Shen, Jianhong
Author_Institution :
Dept. of Math., California Univ., Los Angeles, CA, USA
fDate :
2/1/2001 12:00:00 AM
Abstract :
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 L1) 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
Keywords :
digital filters; filtering theory; image colour analysis; image enhancement; image restoration; iterative methods; noise; nonlinear filters; 1D signals; 2D data; chromaticity; color images; data dependent lowpass filter; digital TV filter; digital image enhancement; global total variational optimization problem; graphs; gray scale images; image denoising; irregular structures; iterations; nonflat image features; nonlinear denoising; nonlinear filter; statistical filters; total variation restoration model; Color; Digital TV; Digital filters; Digital images; Image restoration; Information filtering; Information filters; Noise reduction; Nonlinear filters; Signal restoration;
Journal_Title :
Image Processing, IEEE Transactions on