Title :
A region merging based algorithm for total variation denoising
Author :
Xiaodan, Song ; Fei, Liu ; Yupin, Luo
Author_Institution :
Dept. of Autom., Tsinghua Univ., Beijing, China
Abstract :
In this paper, we propose a region merging based algorithm for total variation (TV) denoising. TV based on denoising is extremely effective for recovering "blocky", possibly discontinuous, functions from noisy data. It is necessary to solve a minimization problem, which results in a nonlinear integro-differential equation of elliptic type. An efficient numerical scheme for solving such an equation is essential. In this paper, the TV denoising energy function is simplified according to the piecewise characteristic which the denoised results reveal. Then the energy is decreased by "region merging" to get a local minimum, which is an estimate of the global minimum. Experimental examples for image denoising are illustrated to show the effectiveness of the method in not only denoising but also segmentation with computational complexity of O(n log n).
Keywords :
elliptic equations; image denoising; image segmentation; integro-differential equations; minimisation; nonlinear differential equations; TV denoising energy function; blocky functions; elliptic equation; image denoising; image segmentation; local minimum; minimization problem; nonlinear integro-differential equation; numerical scheme; piecewise characteristic; region merging based algorithm; total variation denoising; Computational complexity; Image segmentation; Integrodifferential equations; Lagrangian functions; Linear systems; Merging; Noise reduction; Nonlinear equations; Partial differential equations; TV;
Conference_Titel :
Signal Processing, 2002 6th International Conference on
Print_ISBN :
0-7803-7488-6
DOI :
10.1109/ICOSP.2002.1181192
