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Fuzzy kernel refining-based blind simple image motion blurring removal method

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

Active Publication Date: 2018-04-03
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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[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 particularly relates to a fuzzy kernel refining-based blind simple image motion blurring removal method. The method mainly comprises threesteps of: 1, importing an effective strong edge to carry out multiscale fuzzy kernel estimation, and outputting a fuzzy kernel estimation value k and a clear image estimation value I' of each scale according to an input fuzzy image B; 2, forming fuzzy kernel post-processing by hard threshold value processing, connectivity verification and morphological closed operation, and carrying out fuzzy kernel post-processing on the fuzzy kernel estimation k of the highest scale; and 3, carrying out Lapras non-blind convolution removal, and outputting a final fuzzy kernel kR and a final clear image estimation value If. Aiming at the defect that fuzzy kernel estimation is incorrect and is not sparse and continuous enough, the method imports the effective strong edge and the fuzzy kernel post-processing, so as to carry out effective estimation on fuzzy kernels with various forms and various scales and then obtain de-blurring results which are remarkable in effect and 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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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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