自动化学报2012，Vol.38Issue(11)：1804-1814,11.DOI:10.3724/SP.J.1004.2012.01804
多分辨率图像序列的超分辨率重建
Super-resolution Reconstruction for Multi-resolution Image Sequence
摘要
Abstract
A blind super resolution (SR) image reconstruction algorithm based on scale invariant feature transform (SIFT) and image registration is proposed for multi-resolution image sequence taken in various focal lengths. First, SIFT keypoints in images are extracted. Then keypoint descriptors are matched initially under the criterion of vectorial angle cosine and outliers of matches are eliminated by random sample consensus (RANSAC) algorithm to improve registration accuracy. And registered low-resolution (LR) images are mapped onto a high-resolution (HR) grid according to their transform parameters. Finally, space pixels are filled in by a pixel reliability weighted algorithm to reconstruct the image with a higher resolution. Experimental results show that the proposed algorithm can estimate scaling factors accurately and it is effective in affine transformation and is robust to registration errors within a certain range. The algorithm can essentially improve the resolution of multi-resolution image sequence with relatively satisfactory reconstruction result especially under the condition when the number of low-resolution image frames is too small and available information for reconstruction is seriously insufficient.关键词
超分辨率重建/尺度不变特征转换/多分辨率尺度/随机抽样一致性算法/仿射变换Key words
Super resolution (SR) reconstruction/ scale invariant feature transform (SIFT)/ multi-resolution/ random sample consensus (RANSAC) algorithm/ affine transformation引用本文复制引用
李展,张庆丰,孟小华,梁鹏,刘玉葆..多分辨率图像序列的超分辨率重建[J].自动化学报,2012,38(11):1804-1814,11.基金项目
国家自然科学基金(61070090),中央高校基本科研业务费专项资金(21612413,21612414),广东省自然科学基金(10151063201000002),广东省科技计划重大专项项目(2010A080402005),广东省科技计划项目(2010B080701062)资助 （61070090）
