TDI flutter image restoration method based on image block adaptive adjustment

Abstract

The invention discloses a TDI flutter image restoration method based on image block adaptive adjustment. In the TDI flutter remote sensing imaging, the fuzzy kernels of the rows of a flutter image are different because of the line-by-line push-scanning characteristics of a TDI camera, and the line-by-line restoration is used for the flutter image, thereby greatly improving the image restoration effect. When the difference between the fuzzy kernels between rows is smaller, the number of rows of a to-be-restored image block is properly increased at a current line, thereby facilitating the improvement of the restoration effect of the image. When the difference between the fuzzy kernels between rows is bigger, the increase of the number of rows of the image block does not exert remarkable impact on the image restoration effect. However, the increase of the number of rows of the image block will prolong the overall restoration time of the image. Through the construction of a formula of similarity between the fuzzy kernels and the comparison of the difference between the fuzzy kernels between rows of the flutter image, the image block size is used for restoring the current line is determined, and the adaptive adjustment of the image block size is achieved in the line-by-line restoration process of a remote sensing flutter image. The method gives consideration to the restoration time while guaranteeing the image restoration effect.

Description

technical field [0001] The invention belongs to the field of remote sensing image processing, and in particular relates to a method for constructing size-adaptive image blocks row by row according to the similarity degree of fuzzy kernels between rows for TDI flutter image restoration. Background technique [0002] Due to the needs of national security and national defense construction, high-resolution earth observation technology has become one of the key tasks of my country's national defense science and technology industry. one of the important factors. TDI-CCD camera is an important load of visible light imaging on satellites. It is based on multiple exposures to the same target, and increases light energy collection by delay integration. But when the satellite is fluttering, the increase in exposure time will increase the blurring effect of the image. At the same time, because the TDI camera adopts the method of progressive push-broom imaging, there are differences in ...

AI Technical Summary

Problems solved by technology

Wiener filtering and RL algorithm can quickly restore the image, but it will generate a lot of ringing. When the size of the image block to be restored is relatively small, the restoration effect on the image is relatively unstable; the full variation method can ensure the effective suppression of ringing , but it is difficult to recover image details

In the process of deblurring the image line by line, the size of the extracted image block to be restored is generally fixed. If the selected size value is larger, the image restoration time will be longer; if the selected size value is smaller, the image will be restored. Restoration may be less effective

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