A Noisy Image Deblurring Method Based on Mixed Data Fitting and Weighted Total Variation

A mixed data, total variation technology, applied in image enhancement, image analysis, image data processing and other directions, can solve problems that need to be further improved, and achieve the effect of protecting image details, ensuring convergence, and accurate restoration results.

Active Publication Date: 2020-08-14
WUYI UNIV
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Problems solved by technology

[0009] The l1-0.5l2 regularization method was proposed by Lou et al. in the literature "Aweighted difference of anisotropic and isotropic total variation model for image processing.SIAM Image Sciences, 2015, vol.8, pp.1798-1823", by using weighted total variation The difference 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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  • A Noisy Image Deblurring Method Based on Mixed Data Fitting and Weighted Total Variation
  • A Noisy Image Deblurring Method Based on Mixed Data Fitting and Weighted Total Variation
  • A Noisy Image Deblurring Method Based on Mixed Data Fitting and Weighted Total Variation

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Embodiment Construction

[0053] Reference figure 1 , The present invention is based on the method of noise image deblurring based on mixed data fitting and weighted total variation, including the following steps:

[0054] 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 noise the clear image to generate Noise blurred image f;

[0055] Step 2: Build the model and initialize the model parameters;

[0056] The mixed data fitting and weighted total variation solution model is:

[0057]

[0058] 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 denote the weight parameters.

[0059] The model parameters μ=40, λ=1, ρ=2, τ=0.08, the external iteration is set to 2 times, the internal iteration...

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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 are as follows: step 1: input a noise blurred image f with M rows and N columns; step 2: establish a model and Initialize the model parameters; Step 3: Combine the convex subtraction algorithm and the separable Bregman iteration method to solve the target clear image u; Step 4: Determine whether the iteration reaches the stop standard tol, if not, continue the iteration in step 3, Otherwise output the restored image. The model of the present invention adopts mixed data fitting items to ensure better restoration of image details; uses the regularized prior model of weighted total variation to approximate the gradient distribution of natural images, making the restoration results more accurate; uses separable Bregman The iterative method can quickly solve high-quality clear images. The invention has the advantage of keeping the edge texture structure of the reconstructed image well, and can be used for digital image processing in the fields of medicine, 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 exchange. 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 improper operation of shooting equipment and humans, the image quality 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. [0003] The noise b...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00
CPCG06T5/002G06T2207/10004
Inventor 余义斌张家林林治张玉兰郭凯凤
Owner WUYI UNIV
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