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Image motion deblurring method

A motion blur and image technology, applied in the field of image processing, can solve problems such as low reliability and large amount of calculation

Inactive Publication Date: 2017-07-14
CHENGDU UNIV OF INFORMATION TECH
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Problems solved by technology

[0010] The invention provides an image motion blur removal method, which solves the technical problems that the existing image motion blur removal method relies on empirical values ​​when determining the number of models, and has a low degree of reliability and a large amount of calculation. It realizes adaptive selection of the number of models, improves the fitting degree of image gradient distribution, and realizes the technical effect of precise image de-blurring

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Embodiment Construction

[0061] The present invention provides an image de-blurring method, which solves the technical problems that the existing image de-blurring method relies on empirical values ​​when determining the number of models, and has a low degree of reliability and a large amount of calculation. It realizes the adaptive selection of the number of models, improves the fitting degree of the image gradient distribution, and realizes the technical effect of precise image motion blur removal.

[0062] In order to understand the above-mentioned purpose, features and advantages of the present invention more clearly, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that, under the condition of not conflicting with each other, the embodiments of the present application and the features in the embodiments can be combined with each other.

[0063] In the following description, many specifi...

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Abstract

The invention discloses an image motion deblurring method, which includes a first step of establishing infinite student-t distribution mixed models based on the Dirichlet process as an image gradient distribution model and a point spread function model, and obtaining the number of infinite student-t distribution models automatically based on an observation image; and a second step of taking the image gradient distribution model and the point spread function model respectively as an image a priori model and a point spread function priori model, conducting motion deblurring processing on the image using a maximum posteriori estimation method, and estimating a model parameter using variational Bayesian inference. The adaptive selection of the number of models is realized, the degree of fitting of the image gradient distribution is improved, and the technical effect of accurate image motion deblurring is achieved.

Description

technical field [0001] The present invention relates to the field of image processing, in particular to an image motion blur removal method. Background technique [0002] The ill-posedness of the image deblurring problem can be well-conditioned by introducing an image prior model, and establishing a suitable image prior model becomes the key to realizing image deblurring. Image deblurring algorithms based on statistical models have relative advantages. Firstly, the prior distribution model about the image is established, and then the original image, point spread function and parameters are derived based on certain specific criteria, so as to achieve image de-blurring. [0003] Although the shape of the gray distribution of different types of images varies greatly, the shape of the image gradient distribution is very similar. In recent years, studies on the statistical characteristics of natural images have shown that the gradient distribution of natural images obeys heavy-...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00
CPCG06T2207/20076G06T2207/20201G06T5/73
Inventor 符颖吴锡周激流
Owner CHENGDU UNIV OF INFORMATION TECH
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