DocumentCode :
2964888
Title :
Image Enhancement Usingwavelet-Domain Mixture Models
Author :
Shi, Fei ; Selesnick, Ivan W. ; Guleryuz, Onur
Author_Institution :
Polytech. Univ., Brooklyn, NY
fYear :
2006
fDate :
24-27 Sept. 2006
Firstpage :
590
Lastpage :
595
Abstract :
We propose a non-linear mapping function for digital image enhancement in the wavelet domain, which amplifies mid-range coefficients more than small and large coefficients. We derive this function based on a statistical model of the wavelet coefficients. This three-component mixture model describes the coefficients in each subband as a mixture of small, medium, and large coefficients to which different amplification factors are assigned. The model parameters are estimated from each subband using the EM algorithm. The algorithm has a small number of user-specified parameters while can obtain good enhancement results
Keywords :
amplification; expectation-maximisation algorithm; image enhancement; statistical analysis; EM algorithm; amplification factors; digital image enhancement; expectation-maximization algorithm; nonlinear mapping function; statistical model; wavelet-domain mixture models; Boosting; Digital images; Frequency domain analysis; Gaussian distribution; Image enhancement; Laplace equations; Parameter estimation; Wavelet coefficients; Wavelet domain; Wavelet transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Digital Signal Processing Workshop, 12th - Signal Processing Education Workshop, 4th
Conference_Location :
Teton National Park, WY
Print_ISBN :
1-4244-3534-3
Electronic_ISBN :
1-4244-0535-1
Type :
conf
DOI :
10.1109/DSPWS.2006.265492
Filename :
4041133
Link To Document :
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