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A Single Image Blind Motion Blur Removal Method Based on Fuzzy Kernel Refinement

A single image, motion blur technology, applied in the field of image restoration, can solve the problem of incomplete deblurring

Active Publication Date: 2019-11-22
WUHAN UNIV
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Problems solved by technology

[0008] Aiming at the problem of incomplete deblurring caused by inaccurate blur kernel estimation in the process of blind global motion blur removal, the present invention proposes a single image blind motion blur removal algorithm based on blur kernel refinement, and the blur kernel refinement work consists of Effective strong edge and blur kernel post-processing consists of two parts

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  • A Single Image Blind Motion Blur Removal Method Based on Fuzzy Kernel Refinement
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  • A Single Image Blind Motion Blur Removal Method Based on Fuzzy Kernel Refinement

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[0054] In order to make the object, technical solution and advantages of the present invention clearer, the invention will be further described in detail below in conjunction with the accompanying drawings.

[0055] The purpose of the present invention is to output blur kernel estimated value k and clear image estimated value I according to input blurred image B.

[0056] Step 1, multi-scale blur kernel estimation, according to the input blur image B and blur kernel size size k Establish a multi-scale image pyramid, estimate the blur kernel and the intermediate value of the clear image at each scale, including the following sub-steps:

[0057] In step 1.1, the grayscale image is used for blur kernel estimation. If the input blurred image is a color image, it needs to be converted into a grayscale image.

[0058] Step 1.2, construct a multi-scale blur kernel, the number of scales is determined by the input blur kernel size size k Determined, the calculation formula of the min...

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Abstract

The invention belongs to the field of image restoration, and in particular relates to a single image blind motion blur removal method based on blur kernel refinement. This method mainly consists of three steps: in the first step, effective strong edges are introduced for multi-scale blur kernel estimation, and based on the input blur image B, the blur kernel estimate k and clear image estimate I' of each scale are output; in the second step, The fuzzy kernel post-processing consists of hard threshold processing, connectivity testing and morphological closing operations, and the fuzzy kernel post-processing is performed on the highest-scale fuzzy kernel estimate k; the third step is Laplacian non-blind deconvolution, and the final output The blur kernel k R and clear image estimate I f . Aiming at the shortcomings of inaccurate blur kernel estimation and insufficient sparseness and continuity, the present invention introduces effective strong edges and blur kernel post-processing, which can effectively estimate blur kernels of various shapes and scales, thereby achieving significant and Deblurring results that are extremely close to real clear images.

Description

technical field [0001] The invention belongs to the field of image restoration, in particular to a single image blind motion blur removal method based on blur kernel refinement. Background technique [0002] Motion blur caused by relative motion in the imaging process often causes the image to lose important details, greatly weakening the original intuition and simplicity of the image. The prevention work of reducing or evading motion blur as much as possible when shooting images, due to the requirements for shooting equipment and technology, makes this work subject to certain constraints in practical applications. Therefore, the method of image restoration is usually used to process the motion blurred image. This process is called de-motion blurring. It extracts the motion information from the blurred image, and then estimates the hidden clear image according to the image degradation model. [0003] According to the image degradation model, the motion blurred image can be ...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00
CPCG06T2207/20036G06T2207/20192G06T5/75
Inventor 姚剑蒋佳芹涂静敏李礼
Owner WUHAN UNIV
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