Motion blurred image restoration method based on blade edge function and optimal window Wiener filtering

Abstract

The invention discloses a motion blurred image restoration method based on a blade edge function and optimal window Wiener filtering. The method comprises the following steps: firstly, denoising a motion blur image, and detecting a motion blur direction and a motion blur length of the motion blur denoised image by utilizing Radon transformation and a differential autodyne method; and fitting a blade edge function through edge detection to obtain a system degradation function; and finally, obtaining a deblurred restored image by adopting a Wiener filtering method of edge continuation and an optimal window. As the edge function has strong adaptability to various motion blur, and a specific degradation model of the motion blur image does not need to be known, the edge function can be used forconstructing a point spread function and a more accurate system degradation function. According to the method, the motion blur in the image can be effectively removed, the edge error can be effectively reduced, the resolution and the contrast of the restored image can be obviously improved, the details are rich, the ringing effect is avoided, and a certain foundation is laid for further image feature extraction, target detection, mode recognition and the like.

Description

technical field [0001] The invention belongs to the field of signal and information processing, and in particular relates to a motion blurred image restoration method based on an edge function and an optimal window Wiener filter. Background technique [0002] When imaging the target, due to the movement of the carrier, vibration and other reasons, there is relative movement between the camera and the target during exposure, and the resulting imaging blur and smearing effect are image motion, which affects and limits the imaging quality of the mobile camera. an important factor. There are different compensation methods for the image motion caused by the above-mentioned different reasons, which are divided into two categories: hardware compensation and software compensation. Software compensation is based on the mechanism of image degradation, using software to restore the degraded image. This method uses point spread function and Wiener filter to compensate the image motion ...

AI Technical Summary

Problems solved by technology

[0004] To sum up, there is still a lack of a fast and effective deblurring restoration method suitable for distortion during image motion in the prior art.

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