Turbulence-degraded image blind restoration method based on dark channel and Alternating Direction Method of Multipliers

Abstract

The invention relates to a turbulence-degraded image blind restoration method based on dark channel and Alternating Direction Method of Multipliers. The method includes the following steps: firstly on the basis of the multiple dimension theory, in each dimension, applying dark channel prior constraint on an image, applying sparse constraint and energy constrain on a point spread function, then using the coordinate descent method and conducting alternating iteration to estimate a fuzzy kernel and the image in current dimension, if the dimensions arrive at the maximum thereof, a final estimated fuzzy kernel is obtained, finally, in combination with a total variation model, using a derivative Alternating Direction Method of Multipliers to make details of the image restored quickly. According to the invention, the method, by using the dark channel prior information of a clear image as a constraint item, can help a cost function to converge to a clear solution in the iteration process, addresses the susceptibility of obtaining a fuzzy solution by using tapered prior information under the Maximum posterior probability in current blind restoration algorithm, such that the method herein can restore more image details, has less ring effect, and effectively increases restoring quality.

Description

technical field [0001] The invention belongs to a digital image processing method, and relates to a new method for restoring single-frame atmospheric turbulent degraded images, in particular to a blind restoration method for turbulent images based on optimization of dark primary colors and alternating direction multiplier methods, which removes dark primary colors from fog in images The theory is applied to the field of turbulent image blind restoration, and the invention can be used in various military or civilian image deblurring processing systems. Background technique [0002] When the aircraft flies at supersonic speed in the atmosphere, it interacts violently with the atmosphere to form a complex high-temperature turbulent field. This turbulent effect will cause the target image received by the optical system of the aircraft to shift, shake, blur, etc., thereby seriously affecting Its ability to detect, identify and track targets, even fails to detect and identify targ...

AI Technical Summary

Problems solved by technology

Pan applied the dark channel prior theory in image dehazing for the first time to image deblurring, and achieved good results in processing motion blurred images, low-light blurred images and non-uniform blurred images, but the algorithm itself is sensitive to noise , when there is large noise in the blurred image, the processing result of the algorithm has a ringing effect; another way of thinking is to introduce edge selection and use strong edges to restore the image, but this kind of method involves complicated edge selection, how to design "big Gradient preservation and small gradient discarding" rule is a problem, and when the salience of the image is not very strong, the algorithm cannot select a suitable edge to estimate the blur kernel

[0005] It can be seen that the traditional blind restoration method of atmospheric turbulence image, in the case of serious noise or blurring, the visual quality of image restoration is poor, artifacts are prone to occur, and it is sensitive to noise.

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