Acta Optica Sinica, Volume. 35, Issue 1, 110001(2015)
A Method of Super-Resolution Reconstruction for Remote Sensing Image Based on Non-Subsampled Contourlet Transform
An improved method is proposed to solve the existing problem that the fusion process is too simple in non-subsampled contourlet transform (NSCT) super-resolution reconstruction. The magnitude of the spatial frequency reflects the degree of image detail richness, and the improved method uses this magnitude of regional window as the standard of the weight, so the adaptive weighted fusion method is applied to the obtained high frequency by NSCT decomposition of image. The adaptive weighted fusion method and NSCT analysis are assembled to achieve image super-resolution reconstruction, in this process, each corresponding high-frequency image is fused by adaptive weighted fusion method, and the low-frequency image is processed to get a mean. The super-resolution image is acquired by inverse NSCT to both the low frequency images and high frequency images. Through simulation and engineering practice, the improved method proves to be feasible and effective.
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Zhou Jinghong, Zhou Cui, Zhu Jianjun, Fan Donghao. A Method of Super-Resolution Reconstruction for Remote Sensing Image Based on Non-Subsampled Contourlet Transform[J]. Acta Optica Sinica, 2015, 35(1): 110001
Category: Image Processing
Received: Apr. 24, 2014
Accepted: --
Published Online: Dec. 15, 2014
The Author Email: Jinghong Zhou (chxsjkzjh@163.com)