Image restoration method based on smooth Tacker decomposition and high-order tensor Hankering

A repair method and image technology, applied in the field of image repair, can solve problems such as image data distortion, and achieve the effect of taking into account efficiency and good convergence

Pending Publication Date: 2021-01-19
ZHEJIANG UNIV OF TECH
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Problems solved by technology

[0006] In order to solve the problem of visual processing of image data distortion, the present invention extends the Hank structured technology to high-order tensor visual data, and fully considers the essential properties of images, and introduces discrete total variation (Discrete Total Variation, TV d ) regularization factor to integrate it into a unified objective function

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  • Image restoration method based on smooth Tacker decomposition and high-order tensor Hankering
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  • Image restoration method based on smooth Tacker decomposition and high-order tensor Hankering

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Embodiment Construction

[0018] The technical solution of the present invention will be further described below in conjunction with the accompanying drawings.

[0019] An image restoration method based on smooth Tucker decomposition and high-order tensor Hankization, including the following steps:

[0020] Step 1) Input the image to be repaired Determine the area to be repaired in the image and perform a block operation on it. The pixels in the image are divided into known points and unknown points. The known points are the points in the image where the pixels are not 0, and the unknown points are the points where the pixels in the image are 0. point, all unknown points in the image form a set Ω;

[0021] Step 2) constructing high-order tensor Hankization and discrete full variational models;

[0022] Step 3) Combine the image restoration model built in step 2), repair the color image, and finally reconstruct the output high-quality visual data image

[0023] The processing procedure of describe...

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Abstract

The invention discloses an image restoration method based on smooth Tacker decomposition and high-order tensor Hankering. The method comprises the following steps: 1) inputting a to-be-restored imageto determine a to-be-restored area of the image; 2) constructing a high-order tensor Hankering and discrete total variation model; and 3) constructing a smooth Tacker decomposition and high-order tensor Hankering image restoration model in combination with the step 2), restoring the color image, and finally reconstructing and outputting a high-quality visual data image. The method has the advantages that the image processing efficiency and the image restoration accuracy are both considered.

Description

technical field [0001] The invention relates to the field of image processing, in particular to an image restoration method. Background technique [0002] With the rapid development of modern network technology, computer communication and sampling technology, most of the data to be analyzed has a very complex structure. Usually, in the process of image data acquisition, the visual quality will be poor due to the influence of various external factors, for example, the damage of hardware equipment, light and electromagnetic wave interference and so on. In this case, it may also be impossible to directly re-acquire relevant image data due to equipment or time constraints. Therefore, it is a research content with practical application value to restore various blurred, low-resolution, partial pixel loss and other images to obtain high-quality visual data. [0003] Image inpainting is a typical ill-posed problem of image processing, which can be formulated as a missing value est...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00G06T7/11
CPCG06T5/005G06T2207/10024G06T2207/20021G06T7/11
Inventor 郑建炜黄娟娟陈婉君秦梦洁徐宏辉陶星朋
Owner ZHEJIANG UNIV OF TECH
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