Title :
Image denoising based on scale-space mixture modeling of wavelet coefficients
Author :
Liu, Juan ; Moulin, Pierre
Author_Institution :
Beckman Inst. for Adv. Sci. & Technol., Illinois Univ., Urbana, IL, USA
fDate :
6/21/1905 12:00:00 AM
Abstract :
In this paper, we propose a novel hierarchical statistical model for image wavelet coefficients. A simple classification scheme is used to construct a model that captures interscale and intrascale dependencies of wavelet coefficients. Applications to image denoising are presented. We develop a simple algorithm that outperforms other wavelet denoising schemes that exploit first order statistics, or inter- or intra-scale dependencies alone
Keywords :
image classification; wavelet transforms; classification; first order statistics; image denoising; image wavelet coefficients; Compression algorithms; Gaussian distribution; Hidden Markov models; Higher order statistics; Image coding; Image denoising; Image restoration; Noise reduction; Statistical distributions; Wavelet coefficients;
Conference_Titel :
Image Processing, 1999. ICIP 99. Proceedings. 1999 International Conference on
Conference_Location :
Kobe
Print_ISBN :
0-7803-5467-2
DOI :
10.1109/ICIP.1999.821636