关键词: 耦合字典, 最优方向法, 超分辨率重建, 遥感影像, 稀疏表示

Abstract: In order to improve the spatial resolution of remote sensing images, this paper proposes improved joint dictionary learning algorithm. Method of optimal directions is exploited as an updating dictionary algorithm to learn coupled dictionary, and introduces sparse coefficient acquired by learning low resolution dictionary into the high resolution dictionary learning space. Exploiting sparse reconstruction method eventually generates a high resolution remote sensing image. At the same time, this algorithm is optimized, and training samples are automatically intercepted. By experiments, the results show that the proposed approach can achieve better reconstruction quality than existing algorithm in the subjective evaluation criteria. It also demonstrates effectively that the method is much faster than some classic algorithms in the process of learning dictionary, the reconstructed image is more clear and texture structure is more obvious.

Key words: coupled dictionary, method of optimal directions, super-resolution reconstruction, remote sensing imagery, sparse representation