自动化学报Issue(4)：594-603,10.DOI:10.3724/SP.J.1004.2014.00594
基于多尺度结构自相似性的单幅图像超分辨率算法
Single Image Super Resolution Based on Multi-scale Structural Self-similarity
摘要
Abstract
Multi-scale structural self-similarity refers to those similar structures either within the same scale or across different scales coming from the same image, which widely occur in remote sensing images. In this paper, we propose a single image super resolution (SR) method based on multi-scale structural self-similarity, which combines compressive sensing framework and structural self-similarity. In our method, the nonlocal and the pyramid-based K-SVD methods are used to add the extra information hidden in multi-scale structural self-similarity into the reconstructed image in the compressive sensing framework. The advantage of our method is that it only uses a single low-resolution image to promote spatial resolution by fully exploiting the extra information hidden in the image itself. Experimental results demonstrate that our method can improve spatial resolution more effectively compared with the CSSS and the ASDSAR methods.关键词
超分辨率/结构自相似性/多尺度/压缩感知/非局部方法Key words
Super resolution (SR)/structural self-similarity/multi-scale/compressive sensing/nonlocal引用本文复制引用
潘宗序,禹晶,胡少兴,孙卫东..基于多尺度结构自相似性的单幅图像超分辨率算法[J].自动化学报,2014,(4):594-603,10.基金项目
国家自然科学基金(61171117),国家科技支撑计划项目(2012BAH31 B01),北京市教育委员会科技计划重点项目(KZ201310028035)资助@@@@Supported by National Natural Science Foundation of China (61171117), National Science and Technology Pillar Program of China (2012BAH31B01), and Key Project of the Science and Technology Development Program of Beijing Education Com-mittee of China (KZ201310028035) （61171117）
