Scene motion blurred image restoration method in presence of moving object

Abstract

The invention belongs to the field of digital image processing, and in particular discloses a scene motion blurred image restoration method in the presence of a moving object. The method comprises the following steps of: 1, estimating and amending parameters of a motion model of a scene motion blurred image and extracting a moving object blurred image; 2, restoring the motion blurred image: including restoring the scene motion blurred image and restoring the moving object blurred image, wherein the parameters of the motion model of static scene motion blur are estimated by the method in the step 1 and are amended and then the image is restored by using an image restoration method for the scene motion burred image; and 3, fusing restored images: embedding the moving object image restored by the step 2 into the restored scene image, namely fusing the restored moving object image and the restored scene image, and processing the joint part of the restored moving object image and the restored scene image by using a filtering method to enable a joint of the images to be smooth so as to keep integrity of the image.

Description

technical field [0001] The invention belongs to the field of digital image processing, and relates to a method for restoring motion blurred images, in particular to a method for restoring motion blurred images in scenes with moving objects. Background technique [0002] Due to the relative motion between the camera and the subject, the degradation of image quality is called motion blur. Motion blur is a ubiquitous phenomenon in the imaging process. When shooting images on airplanes, fast-moving cars or spacecraft, the relative speed of the subject is too fast or the shaking during shooting will cause motion blur. The phenomenon of motion blur seriously affects the quality of acquired images and brings great difficulties to subsequent processing and analysis. [0003] During the imaging process of the mobile imaging system, the following two situations may occur: (1) There is no moving object in the photographed area. In this case, there is relative motion between the entir...

AI Technical Summary

Problems solved by technology

The non-negative support domain recursive inverse filtering algorithm (NAS-RIF) can well overcome the shortcomings of the poor convergence of the iterative blind deconvolution method and the large amount of calculation of the simulated annealing algorithm.

[0007] The above methods are all aimed at scene motion blurred images. For motion blurred images with moving objects in the scene motion blur, the above restoration methods cannot achieve a good restoration effect.

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