Abstract
The satellite remote image is degraded obviously due to the diffraction-limitation of imaging system and the atmosphere turbulence and etc.. Namely, the observed image blurred by a low-pass filter whose transfer function vanishes beyond imaging system cut-off spatial frequency (omegac ).Processes that achieve the recreation of frequencies beyond the image pass- band are usually referred to as super-resolution algorithms. Although, multi-frame super-resolution has more potential for spatial resolution improvement, as for remote sensing image, single-frame super-resolution is prerequisite in many cases. One remote imaging blurred model is put forward basing on PSF (point spread function) optimal estimation. Then a sub-blocks non-iterative method is adapted to improve the image spatial resolution effectively with only single-frame low spatial resolution image. With this scheme, the high spatial resolution spots5 panchromatic 2.5 m image can be reconstructed from single-frame 5 m panchromatic spots5 image. The MTF is used as impersonal standard to estimate the spatial resolution improvement and image quality. As result, the high frequency detail information and effective band of image are compensated perfectly with SNR improved.
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