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Noise image deblurring method based on mixed data fitting and weighted total variation

A mixed data and deblurring technology, which is applied in image enhancement, image analysis, image data processing, etc., can solve problems that need to be further improved, and achieve good effects of protecting image detail features, ensuring monotonous decrease, and maintaining good edge texture structure

Active Publication Date: 2017-11-21
WUYI UNIV
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Problems solved by technology

[0011] The l1-0.5l2 regularization method was proposed by Lou et al. in the literature "A weighted difference of anisotropic and isotropic total variation model for image processing.SIAM Image Sciences, 2015, vol.8, pp.1798-1823", by using weighted full The variation norm is used to approximate the gradient distribution of natural images, and a higher quality restored image can be obtained. However, this method is more suitable for segmented smooth images, and the protection of image details needs to be further improved.

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  • Noise image deblurring method based on mixed data fitting and weighted total variation

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[0057] refer to figure 1 , the present invention is based on mixed data fitting and weighted total variation noise image deblurring method, comprises the following steps:

[0058] Step 1: Input a clear natural image with M rows and N columns, use a Gaussian blur kernel with a size of 15*15 and a standard deviation of 1.5 and a zero-mean Gaussian white noise with a standard deviation of 0.05 to blur and add noise to the clear image, and then generate Noise blurred image f;

[0059] Step 2: Build a model and initialize model parameters;

[0060] The mixed data fitting and weighted total variation solution model is:

[0061]

[0062] Among them, K is the fuzzy matrix, u is the restored image to be solved, D x 、D y Denote the difference in the horizontal direction and the difference in the vertical direction, respectively, and μ and ρ represent the weight parameters.

[0063] Model parameters μ = 40, λ = 1, ρ = 2, τ = 0.08, the outer iteration is set to 2 times, the inner ...

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Abstract

The invention discloses a noise image deblurring method based on mixed data fitting and weighted total variation. The implementation steps include 1. inputting a noise blurred image f of M rows and N columns; 2. establishing a model and initializing model parameters; 3. combining a convex subtraction algorithm and a separable Bregman iteration method to solve a target clear image u; and 4. judging whether iteration reaches a stop standard tol, and if the iteration does not reach the stop standard, continuing to circulate iteration in the Step 3, and otherwise outputting a restored image. The model in the method adopts a mixed data fitting term, thereby ensuring that image details are well restored; a weighted total variation regularization prior model is utilized to perform approximate simulation on gradient distribution of a natural image, so that a restoration result is relatively acute; and the separable Bregman iteration method is utilized, and thus a high-quality clear image can be solved rapidly. The noise image deblurring method provided by the invention has the advantage of good reconstructed image edge texture structure maintenance, and can be used for digital image processing in the fields of medical science, astronomy, video multimedia and the like.

Description

technical field [0001] The invention relates to the technical field of digital image processing, in particular to a noise image deblurring method based on mixed data fitting and weighted total variation, which can be used for digital image processing in the fields of medical imaging, astronomical influence, video multimedia and the like. Background technique [0002] The quality of digital images plays a vital role in the process of human information communication. High-quality images bring accurate content and information, while low-quality images will lose a lot of important information. However, in the process of shooting, collecting, storing, transmitting and storing digital images, due to many factors such as shooting equipment and improper human operation, the quality of the image is degraded and cannot truly reflect the object being photographed. Noise image deblurring as an image preprocessing method directly affects the effect of image subsequent processing. [00...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00
CPCG06T2207/10004G06T5/70
Inventor 余义斌张家林林治张玉兰郭凯凤
Owner WUYI UNIV
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