多分辨率图像序列的超分辨率重建  

Super-resolution Reconstruction for Multi-resolution Image Sequence

作　　者：李展[1] 张庆丰[1] 孟小华[1] 梁鹏[2] 刘玉葆[3] 

机构地区：[1]暨南大学信息科学与技术学院计算机科学系,广州510632 [2]广东技术师范学院计算机科学学院,广州510665 [3]中山大学信息科学与技术学院计算机科学系,广州510275

出　　处：《自动化学报》2012年第11期1804-1814,共11页Acta Automatica Sinica

基　　金：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~~

摘　　要：针对不同焦距下拍摄的多分辨率尺度的图像序列,本文提出了一种基于尺度不变特征转换(Scale invariant feature transform,SIFT)和图像配准的超分辨率(Super resolution,SR)图像盲重建算法.首先提取图像SIFT特征点,然后用向量夹角余弦进行特征描述符向量的初匹配,并用随机抽样一致性(Random sample consensus,RANSAC)算法消除误匹配提高配准精度.计算变换参数后,将低分辨率图像(Low-resolution,LR)像素点映射到高分辨率(How-resolution,HR)网格,最后利用像素可信度加权算法填充缺失像素值,重建更高分辨率的图像.实验表明,本文算法能精确估计图像序列的缩放因子,可以有效处理仿射变换模型,对配准误差也具有一定的鲁棒性.算法从实质上提高了多分辨率尺度图像序列的分辨率,尤其在低分辨率帧数较少可用于重建的信息量严重不足时也能获得比较满意的重建效果.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 iu 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 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]