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Image blind deblurring method based on L0 regularization and fuzzy kernel aftertreatment

A blind deblurring and blurring image technology, applied in the field of image restoration, can solve problems such as excessive noise, poor image restoration effect, and inconformity with the objective characteristics of blur kernel sparsity

Active Publication Date: 2017-09-08
SUN YAT SEN UNIV
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  • Application Information

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Problems solved by technology

In the existing technical methods, the L2 regularization term of the fuzzy kernel is usually introduced into the optimization model. This method can quickly solve the problem, but the obtained fuzzy kernel is relatively dense, which does not meet the objective characteristics of the sparseness of the fuzzy kernel. The final restored poor image quality
There are also some methods that add the L1 regularization term of the blur kernel to the optimization model, but this will make the blur kernel contain more noise, and the image restoration effect is relatively poor

Method used

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  • Image blind deblurring method based on L0 regularization and fuzzy kernel aftertreatment
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  • Image blind deblurring method based on L0 regularization and fuzzy kernel aftertreatment

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Embodiment 1

[0069] Such as figure 1 As shown, a method for blind image deblurring based on L0 regularization and blur kernel post-processing includes the following steps:

[0070] S1: Determine whether the input original blurred image is a grayscale image, if not, transform it into a grayscale image;

[0071] S2: Construct an optimization model to solve the fuzzy kernel, and introduce the L0 regular term into the model. The model is shown in formula (1):

[0072]

[0073] Among them, β, μ and λ are weight parameters, x is a blurred image, y is a clear image, k is a blur kernel, *

[0074] is the convolution operator, Indicates the gradient operation;

[0075] S3: extracting the skeleton from the blur kernel obtained in step S2, and weighting according to the distance from each non-zero point to the skeleton, and recalculating the size of each point in the blur kernel;

[0076] S4: Using the new blur kernel obtained in step S3, use a non-blind deblurring method to restore each chan...

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Abstract

The invention discloses an image blind deblurring method based on L0 regularization and fuzzy kernel aftertreatment. The method comprises the following steps that: in an optimization model of image restoration, introducing prior information related to an image gradient, a fuzzy kernel pixel and fuzzy kernel gradient sparsity, and presenting in an L0 regular term form; then, carrying out aftertreatment on the fuzzy kernel obtained by optimization calculation according to the objective characteristics of the fuzzy kernel, carrying out human intervention to make up deficiencies brought by the optimization model, and enabling the fuzzy kernel and an intermediate image obtained by restoration to more conform to reality so as to finally further improve the quality of a restored image; and finally, adopting a semi-secondary split method to solve the optimization model. The method has a simple solution, a calculated amount is reduced, meanwhile, a pyramid model is combined to carry out layered calculation, and therefore, the method is high in robustness and has a wide applicable range.

Description

technical field [0001] The present invention relates to the technical field of image restoration, and more specifically, to a method for blind image deblurring based on L0 regularization and blur kernel post-processing. Background technique [0002] With the development of society, images have become an important way of information dissemination and acquisition. However, due to the limitations of the imaging system, factors such as dust in the air, light, and weather during the imaging process will have a negative impact on the quality of the image, and image quality degradation is common. At the same time, the degradation of image quality will cause the loss of a large amount of information, and the image with degraded quality is very inconvenient in actual use, and even cannot be used directly. Therefore, it is of great significance to recover clear and high-quality images from degraded images. [0003] Blind image deblurring (blind image deconvolution) is one of the imp...

Claims

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Application Information

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IPC IPC(8): G06T5/00
CPCG06T5/73
Inventor 刘红梅张凤君卢伟
Owner SUN YAT SEN UNIV
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