摘要
文中把MAP联合求解模型应用到遥感图像序列的超分辨率重建中来,并针对其在边缘保持能力和收敛复杂度方面的局限性,做出如下的改进:运动估计阶段使用SIFT特征算子和光流法相结合提取运动矢量;引入一个二进制掩膜变量,减少模糊边缘效应;迭代重构采用EM算法,使最终结果收敛到一个稳定的最优解。最后的实验结果也表明,针对具有挑战性的低分辨率遥感图像序列的输入,我们的方法可以产生更加清晰和更高分辨率的重建结果。
In this paper,the joint MAP model is applied to the super-resolution reconstruction of the remote sensing image sequence,and the following improvements are made to its limitations in the edge preserving and the convergence complexity：SIFT feature operator and optical flow methods are combined to extract the motion vector in motion estimation stage;introducing a binary mask variable to reduce the fuzzy edge pixels;we use EM iterative algorithm to converge to a stable optimal solution. The final experimental results also show that our approach can produce a clearer and higher resolution reconstruction result for the input of challenging low resolution remote sensing image sequences.
作者
胡龙珍
尹增山
高爽
HU Long-zhen;YIN Zeng-shan;GAO Shuang(Shanghai Institute of Microsystem and Information Technology,Chinese Academy of Sciences,Shanghai 200050,China;Shanghai Engineering Center for Microsatellites,Shanghai 201203,China;University of Chinese Academy of Sciences,Beijing 100049,China)
出处
《电子设计工程》
2018年第21期180-184,189,共6页
Electronic Design Engineering
