基于帧间预测和联合优化的干涉多光谱图像压缩感知重建算法  

Compressed Sensing Reconstruction Algor ithm of Interferometric Multi-SpectralImage Based on Interframe Prediction and Joint Optimization

作　　者：孔繁锵[1] 井庆丰[1] 计振兴[1] 

机构地区：[1]南京航空航天大学航天学院,南京210016

出　　处：《南京航空航天大学学报》2013年第2期225-231,共7页Journal of Nanjing University of Aeronautics & Astronautics

基　　金：江苏省自然科学基金(BK2010498)资助项目;国家自然科学基金(61102069;61201365)资助项目;中国博士后科学基金(20110491421)资助项目;南京航空航天大学青年科技创新基金(NS2012027;NS2013085)资助项目;南京航空航天大学基本科研业务费专项科研(NP2011048)资助项目

摘　　要：根据干涉多光谱图像的特点,提出一种基于帧间预测和联合优化的干涉多光谱图像压缩感知重建算法。在干涉多光谱图像重建中,根据干涉多光谱图像的帧间相关特性,通过帧间预测除去当前帧图像测量数据中帧间相关的测量数据,并利用干涉多光谱图像预测去相关以后的残差图像的熵值较小的特征,用基于联合优化的重建方法重建帧间预测残差图像,最后得到当前帧的恢复图像。实验结果表明,在相同观测数目下,本文算法与其他方法相比,有效提高了图像重建质量,而且计算复杂度较低。According to the characteristic of interferometric multi-spectral image, a novel compressed sensing reconstruction algorithm for interferometric multi-spectral image is proposed based on interframe prediction and joint optimization. According to the apparent correlations between the interferometric multi-spectral image series, the interframe correlation redundancy is removed from the measurement data of current image by interframe prediction in the reconstruction process. The obtained residual measurement data is recovered by the joint optimization method utilizing the smaller entropy of residual image. Finally, the reconstruction image of current frame is acquired. Experimental results show that the proposed algorithm can improve the reconstruction performance better than reconstruction algorithms with the same measurement number, and efficiently reduce the cost of computation in the reconstruction process.

关 键 词：干涉多光谱图像 压缩感知 信号重建 帧间预测 联合优化 

分 类 号：TN919.81[电子电信—通信与信息系统]