Remote Sensing Images Super Resolution Reconstruction Based on Multi-scale Detail Enhancement

doi:10.11947/j.AGCS.2016.20150451

Abstract

Abstract: The existing methods are hard to highlight the details after super resolution reconstruction, so it is proposed a super-resolution model frame to enhance the multi-scale details. Firstly, the sequence images are multi-scale deposed to keep the edge structure and the deposed multi-scale image information are differenced. Then, the smoothing information and detail information are interpolated, and a texture detail enhancement function is built to improve the scope of small details. Finally, the coarse-scale image information and small-medium-scale information are confused to get the premier super-resolution reconstruction result, and a local optimizing model is built to further promote the premier image quality. The experiments on the same period and different period remote sensing images show that the objective evaluation index are both largely improved comparing with the interpolation method, traditional total variation(TV)method,and maximum a posterior(MAP) method. The details of the reconstruction image are improved distinctly. The reconstruction image produced using the proposed method provides more high frequency details, and the method proves to be robust and universal for different kinds of satellite remote sensing images.

Key words: super resolution reconstruction, detail enhancement, multi-scale decomposition, image fusion

CLC Number:

P236

ZHU Hong, SONG Weidong, TAN Hai, WANG Jingxue. Remote Sensing Images Super Resolution Reconstruction Based on Multi-scale Detail Enhancement[J]. Acta Geodaetica et Cartographica Sinica, 2016, 45(9): 1081-1088.

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