CASIA OpenIR  > 智能制造技术与系统研究中心  > 多维数据分析
Color image superresolution using multi-channel data fusion
Zhao Shubin; Han Hua; Peng Silong
2003
Conference NameThird International Symposium on Multispectral Image Processing and Pattern Recognition
Pagespp 39-44
Conference Date2003/10/20-2003/10/22
Conference Place中国Beijing China
AbstractThis paper presents a wavelet-domain Hidden Markov Tree(HMT)-based color image superresolution algorithm using multi-channel data fusion. Because there exists correlations among the three channels of a RGB color image a channel by channel superresolution method almost certain leads to color distortion. In order to solve this problem first the low-resolution color image is converted into a gray-scale image using the spatially-adaptive approach presented in this paper and the resulting gray-scale image must reflect the human perception of edges in the color image; then by superresolving this gray-scale image a high-resolution image is obtained; finally wavelet-domain HMT-based image superresolutions are performed for the three channels of the low-resolution color image using the same posterior state probabilities which reflect the hidden states of the wavelet coefficients of the high-resolution gray-scale image obtained before and thus the resulting high-resolution color image is what we desired. Becasue the correlations among the three channels of a RGB color image are considered there are no color distortions in the reconstructed high-resolution image. Experimental results show that the reconstructed color images have high PSNR and are of high visual quality.
KeywordData Fusion Super Resolution Wavelets Distortion
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/12902
Collection智能制造技术与系统研究中心_多维数据分析
Corresponding AuthorZhao Shubin
Recommended Citation
GB/T 7714
Zhao Shubin,Han Hua,Peng Silong. Color image superresolution using multi-channel data fusion[C],2003:pp 39-44.
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