Title :
Wavelet Denoising of Multicomponent Images, using a Noise-Free Image
Author :
Scheunders, Paul ; De Backer, Steve
Author_Institution :
Dept. of Phys., Antwerp Univ., Belgium
Abstract :
In this paper, a Bayesian wavelet denoising procedure for multicomponent images is proposed. The procedure makes use of a noise-free single component image as prior information. The prior model for the wavelet coefficient marginals is a Gaussian scale mixture (GSM) model. Experiments on color images and multispectral remote sensing images are conducted to validate the procedure.
Keywords :
Bayes methods; Gaussian processes; image colour analysis; image denoising; remote sensing; wavelet transforms; Bayesian wavelet denoising; GSM model; Gaussian scale mixture; color image; multicomponent image; multispectral remote sensing image; Bayesian methods; Discrete wavelet transforms; GSM; Hyperspectral imaging; Hyperspectral sensors; Multispectral imaging; Noise reduction; Principal component analysis; Remote sensing; Spatial resolution; Bayesian wavelet denoising; multicomponent images;
Conference_Titel :
Image Processing, 2006 IEEE International Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
1-4244-0480-0
DOI :
10.1109/ICIP.2006.313023
