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Color image reconstruction method based on tensor enhancement technology of local data block

A technology of local data and color images, applied in the field of image processing, can solve problems such as disrupting the data structure, affecting the visual effect of the image, and artifact blocks.

Active Publication Date: 2021-07-06
HEBEI UNIV OF TECH
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Problems solved by technology

Although tensor enhancement technology can increase the data dimension and greatly improve the accuracy of image restoration, the current addressing mode based on this technology completely disrupts the data structure for each pixel. Serious artifact blocks will be generated, seriously affecting the visual effect of the image, and image reconstruction cannot be achieved with high accuracy

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  • Color image reconstruction method based on tensor enhancement technology of local data block
  • Color image reconstruction method based on tensor enhancement technology of local data block
  • Color image reconstruction method based on tensor enhancement technology of local data block

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Embodiment Construction

[0032] The technical solutions of the present invention will be described in detail below in conjunction with specific drawings and embodiments, which are not intended to limit the scope of protection of the present application.

[0033] The present invention is a color image reconstruction method based on tensor enhancement technology of local data blocks (method for short, see Figure 1-4 ), the method includes the following steps:

[0034] Step 1: The image to be reconstructed has a single size of 2 p ×2 p ×3 standard color image as an example, denoted as is the field of real numbers, p is a positive integer; record The image after random missing part of the data is is the random missing operator Ω acting on got on, The gray value of the missing data is 0, record the known data in The position in is the index position;

[0035] Use the local data block as the tensor enhancement unit to perform structured addressing, rearrange the pixels of the image to be re...

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Abstract

The invention relates to a color image reconstruction method based on a tensor enhancement technology of a local data block, which comprises the following steps: 1, dividing a to-be-reconstructed image into local data blocks, carrying out structured addressing by taking the local data blocks as tensor enhancement units, converting the to-be-reconstructed image from three-dimensional data into high-dimensional data, and obtaining a high-order tensor; 2 reconstructing the high-order tensor by using a tensor chain nuclear norm minimization model to obtain a reconstructed tensor; and 3 carrying out inverse operation of the step 2 on the reconstructed tensor according to an index position to obtain a converted image, calculating the gray value of each pixel point of the converted image, and restoring the size of the converted image to the original size of the to-be-reconstructed image to complete the reconstruction of the color image. According to the method, a local data block is used as a tensor enhancement unit for structured addressing, the local data block is used as a whole for operation, the complete structure of the local data is reserved, and artifact blocks caused by thorough disruption of the data structure on a reconstructed image are reduced.

Description

technical field [0001] The invention belongs to the technical field of image processing, in particular to a color image reconstruction method based on the tensor enhancement technology of local data blocks. Background technique [0002] As digital image processing is widely used in communication, medicine, aerospace and other fields, as an important research field of digital image processing, image restoration has gradually become a research hotspot. Since color images are a natural form of tensors, the reconstruction problem of color images can be regarded as a tensor completion problem. [0003] The Tensor Train (TT) decomposition model solves the problem of low efficiency of the rank minimization scheme in capturing tensor global information due to the unbalanced expansion matrix size of the traditional tensor decomposition model by virtue of a more balanced matrix method. The tensor chain decomposition model can It fully captures the correlation between data of differen...

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Application Information

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IPC IPC(8): G06T5/00
CPCG06T2207/10004G06T2207/10024G06T5/90
Inventor 何静飞郑绪南高鹏周亚同
Owner HEBEI UNIV OF TECH
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