CASIA OpenIR  > 智能制造技术与系统研究中心  > 多维数据分析
Wavelet-domain least squares based image superresolution
Zhao Shubin; Zhang Peng; Peng Silong
2003
Conference NameProceedings of the Third International Conference on Wavelet Analysis and Its Applications (WAA)
Pagespp 269-274
Conference Date2003/5/29-2003/5/31
Conference Place中国Chongqing China
AbstractThis paper proposes a wavelet-domain least-squares based algorithm for image super-resolution. Based on the fact of the self-similarity of multscale edges it is possible to predict the three subband wavelet coefficients. Once the wavelet coefficients are obtained high-resolution images can be reconstructed using inverse DWT. Because the algorithm properly preserves the local regularity around edges the induced images are of high visual quality. Besides since we only need to predict the wavelet coefficients near edges the algorithm is computationally efficient. Finally quantitative error analyses are provided and several images are shown for subjective assessment.
Keyword
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/12900
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,Zhang Peng,Peng Silong. Wavelet-domain least squares based image superresolution[C],2003:pp 269-274.
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