Image deblurring method and device and electronic equipment

Abstract

The embodiment of the invention provides an image deblurring method and device and electronic equipment. The method comprises the steps that a target blurred image to be deblurred and depth information corresponding to the target blurred image are acquired; determining a target depth value of the target blurred image based on the depth information corresponding to the target blurred image, the target depth value being used for representing an average depth of each pixel point contained in the target blurred image; determining a target blurred kernel parameter corresponding to the target depthvalue based on a pre-constructed corresponding relationship between the depth value of the blurred image and the blurred kernel parameter; generating a target fuzzy kernel with a target fuzzy kernel parameter; and performing a deconvolution operation on the target blurred image by using the target blurred kernel to obtain a deblurred image corresponding to the target blurred image. Through the technical scheme provided by the embodiment of the invention, the efficiency of determining the blurred kernel of the blurred image can be improved, and the deblurred image corresponding to the blurred image can be quickly obtained.

Description

technical field [0001] The present invention relates to the technical field of image processing, in particular to an image deblurring method, device and electronic equipment. Background technique [0002] When capturing an image, the captured image may be a blurred image due to the movement of the object or the inaccurate focus of the camera. In order to make the blurred image clear, it is necessary to perform image deblurring processing on the blurred image. [0003] Usually, the blurred image is considered to be obtained by convolving the blur kernel of the original clear image. Correspondingly, the process of image deblurring is the process of deconvolving the blurred image with the blur kernel, where the blur kernel is usually a matrix . Image deblurring can be divided into two categories, namely non-blind image deblurring and blind image deblurring. Wherein, the image deblurring process with known blur kernel can be called image non-blind deblurring; the image deblur...

AI Technical Summary

Problems solved by technology

It can be seen that the blur kernel determination method used to determine the blur kernel of the blurred image is relatively complicated, resulting in low efficiency in determining the blur kernel of the blurred image, resulting in low efficiency of image blind deblurring

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