Sparse characteristics based video image de-blurring method

A technology for video images and sparse features, applied in image enhancement, image data processing, instruments, etc., can solve problems such as rapid solution tool failure, multiple solutions, local optimal solutions, etc.

Active Publication Date: 2016-12-07
PEKING UNIV
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Problems solved by technology

However, the biggest problem with using this constraint is that this constraint is a non-convex constraint, that is to say, after using this type of constraint, there may be multiple solutions and local optimal solutions, and the fast solution tool is in this will fail on the issue

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  • Sparse characteristics based video image de-blurring method
  • Sparse characteristics based video image de-blurring method
  • Sparse characteristics based video image de-blurring method

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[0050] In order to make the purpose, technical solutions and advantages of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. It should be understood that the specific The examples are only used to explain the present invention, not to limit the present invention. The described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0051] Such as figure 1 As shown, the video image deblurring method based on the sparsity feature includes a modeling step S1, establishing a deblurring model constrained by weighted total variation regularization; and a solving step S2, ...

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Abstract

The invention provides a sparse characteristics based video image de-blurring method, comprising the following steps: a modeling step of establishing a de-fuzzy model of weighted total variation regularization constraint described in the figure wherein / x represents a restored clear image, B a fuzzy kernel, y a generated blur image, [miu] an adjustable parameter, W a diagonal matrix of weights, and Vx includes the first-order differentials in the transverse, longitudinal and diagonal directions; and a solving step where an alternating iterative method is used to obtain the updated pixel weights of the / x and repetitive iterations are performed until the / x is converged. According to the invention, the de-blurring of a blurred image can be realized for a restored clear image. Moreover, the non-convex constraint model is improved through the method of weight assignment, and the convex optimization model is established to make the first-order differential constraint model of the image sparser and the possibility for rapid solution for the model.

Description

technical field [0001] The invention belongs to the technical field of video image processing, in particular to a method for deblurring video images based on sparse characteristics. Background technique [0002] Image deblurring refers to the method of studying how to use a computer to restore a blurred digital image back to a clear image. [0003] Video deblurring refers to the method of processing the blurred video sequence caused by shooting into a clear sequence. [0004] The popularity of digital imaging equipment (digital cameras, digital video cameras, etc.) makes digital images more and more widely used. Inaccurate focusing during the shooting process, atmospheric blur in the air, and shaking during shooting will all cause unclear images. Faced with this situation, we need to use an image processing technology to turn this unclear image into a clear image. And this signal processing technology is the deblurring algorithm. [0005] Deblurring algorithms are mathem...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00
CPCG06T5/003
Inventor 贾惠柱柏园超解晓东杨长水陈瑞高文
Owner PEKING UNIV
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