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High-energy X-ray image blind restoration method and system

An X-ray and blind restoration technology, applied in the field of image processing, can solve problems such as insufficient accuracy of blur kernel estimation and poor restoration effect of high-energy X-ray images

Active Publication Date: 2021-05-18
HOHAI UNIV
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Problems solved by technology

[0004] The technical problem to be solved by the present invention is to overcome the defects of poor restoration effect of high-energy X-ray images and insufficient accuracy of blur kernel estimation in the prior art, and provide a blind restoration method of high-energy X-ray images

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[0016] The present invention will be further described below. The following examples are only used to illustrate the technical solution of the present invention more clearly, but not to limit the protection scope of the present invention.

[0017] A method for blind restoration of high-energy X-ray images, comprising the following steps:

[0018] Step 1: Obtain the high-energy X-ray blurred image b, and build a blind image restoration model; input the high-energy X-ray blurred image b into the pre-built image blind restoration model, and initialize the blur kernel k 0 , and according to the blur kernel k 0 Set the maximum iteration scale L max And the maximum number of iterations N per scale max , obtain the objective function one about the clear image variable l to be restored, the objective function two of the fuzzy kernel variable k to be solved;

[0019] Specifically include the following steps:

[0020] Mathematically, image degradation can be expressed by the convol...

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Abstract

The invention discloses a high-energy X-ray image blind restoration method and system. The method comprises the following steps: firstly, proposing definition of an image region extreme value according to the characteristic that high-energy X-ray image gray level distribution is concentrated and continuous; then, constraining the regional extreme value and the blurring kernel of the image by using an l0 norm, and constructing an image blind restoration model on an MAP framework in combination with the gradient prior of the image; thirdly, alternately solving a clear image and a fuzzy kernel through a semi-quadratic splitting method and fast Fourier transform, and accelerating the solving of sub-problems by using linear approximation and an acceleration conjugate gradient method; and finally, obtaining the main structure information of the preliminarily estimated blurring kernel through a skeleton extraction and traversal method, constructing a continuous function in a blurring kernel cross sliding window for optimization, and performing non-blind deconvolution on the blurring image by using the optimized blurring kernel k, to obtain a clear image. According to the method, the system blurring in the high-energy X-ray image is better removed, the quality of the image is improved, and a more accurate blurring kernel is estimated for nonlinear reconstruction of the image.

Description

technical field [0001] The invention relates to a high-energy X-ray image blind restoration method and system, belonging to the technical field of image processing. Background technique [0002] Among the current technologies for diagnosing and testing nuclear weapons, high-energy X-ray radiography is often used to diagnose the density information and structural information changes of objects during the explosion and bombing process, which is of great significance in the field of national defense. The quality of high-energy radiography images significantly affects the performance of diagnostic tests. Due to the complexity of its imaging system, various degradation factors are prone to occur in multiple processes such as imaging, transmission, and reception. Therefore, imaging has problems such as large noise, distortion, and serious blur, which makes the image quality poor. Removing the effects of blur and degradation to obtain higher quality images is the premise of X-ray ...

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Application Information

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IPC IPC(8): G06T5/00
CPCG06T2207/10116G06T2207/20076G06T5/73
Inventor 王肖霖吴艺李庆武许金鑫王纯款张杉马云鹏
Owner HOHAI UNIV
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