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A noise image completion method based on weighted SLETEN norm minimization

A technology of Slater and En-norm, applied in the field of digital image processing, can solve problems such as ineffective processing, and achieve broad market prospects and application value, good visual effects and quantitative analysis effects.

Active Publication Date: 2019-06-21
BEIHANG UNIV
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Problems solved by technology

[0009] The above design methods of image completion either consider low-rank prior modeling or non-local statistical modeling. Some methods also use full variational norms to ensure local smoothness, but none of the above methods can effectively deal with noise and Images with random missing pixels

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  • A noise image completion method based on weighted SLETEN norm minimization
  • A noise image completion method based on weighted SLETEN norm minimization
  • A noise image completion method based on weighted SLETEN norm minimization

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Embodiment Construction

[0042] In order to better understand the technical solutions of the present invention, the implementation manners of the present invention will be further described below in conjunction with the accompanying drawings.

[0043] Such as figure 1 As shown, the present invention is a noise image complement method based on weighted Slater norm minimization, and the steps are as follows:

[0044] Step 1: Divide the image to be completed into the same size as n small blocks, each of which is a target block, use the sliding window technology to search m similar blocks for each target block (the smaller the Euclidean distance, the greater the similarity between blocks), these similar blocks consist of A similarity group of target blocks. Preliminary image completion is performed under the low-rank framework based on the weighted Slattern norm method, and the optimization problem to be solved is as follows:

[0045]

[0046] where R=X-B,Z i That is, the ith similarity group matr...

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Abstract

The invention relates to a noise image completion method based on weighted SLETEN norm minimization, which comprises the following specific steps: for an image restoration problem with a certain variance noise and a certain proportion of random pixel loss at the same time, firstly, constraining low-rank priori of an image by using a weighted SLETEN norm; ensuring the local smoothness of the complemented image through the response sparsity of the constrained image to the analysis operator; And finally, constraining the non-local self-similarity of the image by utilizing a non-local statisticalmodel. The above three steps are iterated continuously until the algorithm reaches a convergence condition, and a final completion result can be obtained. By means of the method, images with differentnoise levels and pixel missing of various proportions can be well recovered, and a good visual effect and a good quantitative analysis effect can be achieved even when the noise level is high. The method can be widely applied to noisy image completion, and has wide market prospects and application values.

Description

[0001] 【Technical field】 [0002] The present invention relates to a noise image completion method based on the minimization of the weighted Slater norm, in particular to a noise image completion method with the minimization of the weighted Slattern norm with local and global constraints, the weighted Slattern norm The technology of number minimization and image completion has a wide range of applications in the field of image applications, and belongs to the field of digital image processing. [0003] 【Background technique】 [0004] The purpose of image completion is to complement the missing pixels in the image. It has applications in various fields such as medical imaging, hyperspectral image processing, image coding and transmission, etc. It is an important topic in computer vision and image processing, so it has attracted wide attention. Research. [0005] The prior information of the image has a great influence on the performance of the image completion algorithm. In ge...

Claims

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Application Information

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IPC IPC(8): G06T5/00G06T5/10
Inventor 白相志张宇轩樊蕊蕊魏光美
Owner BEIHANG UNIV
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