中文摘要：

针对卫星云图在接收及传输过程中受噪声、大气湍流、太阳风暴及卫星轨道漂移等影响造成的云图数据破损,提出了一种联合块匹配与稀疏表示的卫星云图修复方法。首先,根据破损区域的优先权值确定待修复像素,对该像素的邻域进行分块处理。然后,利用待修复块与各匹配块之间的结构相似度,建立相应的冗余字典;通过求解稀疏表示问题修复该破损区域。最后,沿着等照度线不断更新优先权值,实现整幅图像的修复。实验结果表明,提出的方法不仅能避免传统偏微分方程（PDE）修复法所导致的结构丢失,也能很好地改善基于纹理填充修复方法所导致的修复不足及块效应现象。测试结果显示：在云图存在局部区域缺失时,修复后云图的峰值信噪比（PSNR）比匹配追踪法及总变分法的修复结果平均提高了8.50dB和0.28dB,而且在纹理细节及边缘区域具有更好的视觉效果。

英文摘要：

For some defects of satellite cloud images caused by noises,atmospheric turbulence,solar storms and satellite orbit drifts in the receiving and transmission process,a novel satellite cloud image inpainting method using patch matching and sparse representation was proposed.Firstly,apixel to be inpainted was searched according to the priority of the damaged area.The neighborhood of this pixel was divided into patches,and a redundant dictionary was constructed by calculating the structural similarity of inpainting patch and matching patches.Then the damaged area was repaired by solving a sparse representation problem.Finally,the whole cloud image was inpainted by updating priority along an isophote repeatedly.The experimental results show that the proposed method can not only avoid the structure missing from the traditional Partial Differential Equation（PDE）method,but also can improve the texture details and blocking effect of the texture filling repair method.For the cloud image with local defects,the inpainted image by proposed method can improve Peak Signal to NoiseRatio（PSNR）by 8.50dB and 0.28dB as compared to Matching Pursuit（MP）method and Total Variation（TV）method respectively.It shows better visual effects on texture details and edge regions.