DocumentCode :
2496717
Title :
An improved NAS-RIF algorithm based on the wavelet denoising and image segmentation
Author :
Tao, Qingchuan ; Luo, Dai-sheng ; He, Xiao-hai
Author_Institution :
Coll. of Electron. Inf., Sichuan Univ., Chengdu, China
Volume :
5
fYear :
2003
fDate :
2-5 Nov. 2003
Firstpage :
2860
Abstract :
An improved method is presented in this paper to overcome drawbacks of the original NAS-RIF algorithm. To begin with, the wavelet denoising technique is used to preserve the edge feature of the degraded image, restrain noise amplification, and increase the Signal-to-Noise Ratio (SNR); then, the image segmentation technique is applied in each iteration to find the precise support region of the object, where the non-uniform background is replaced by the mean of the background; the algorithm resetting of the convergence of the conjugate gradient is also employed here to speed up the convergence rate. The improved algorithm is experimentally shown to have better restoration effect and faster convergence rate.
Keywords :
conjugate gradient methods; convergence; filtering theory; image denoising; image segmentation; recursive filters; NAS-RIF algorithm; SNR; conjugate gradient; convergence rate; image segmentation; precise support region; restoration effect; restrain noise amplification; signal to noise ratio; wavelet denoising; Additive noise; Background noise; Convergence; Degradation; Image restoration; Image segmentation; Iterative algorithms; Machine learning algorithms; Noise reduction; Signal to noise ratio;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2003 International Conference on
Print_ISBN :
0-7803-8131-9
Type :
conf
DOI :
10.1109/ICMLC.2003.1260045
Filename :
1260045
Link To Document :
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