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A Sparse Coding Method to Solve the Similarity Preservation Problem in Image Super-resolution Reconstruction

A technology of super-resolution reconstruction and sparse coding, which is applied in image coding, graphics and image conversion, image data processing, etc.

Inactive Publication Date: 2019-07-30
SHANDONG UNIV
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Problems solved by technology

[0005] Aiming at the deficiencies of the prior art, the present invention provides a sparse coding method that solves the similarity preservation problem in image super-resolution reconstruction;

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  • A Sparse Coding Method to Solve the Similarity Preservation Problem in Image Super-resolution Reconstruction
  • A Sparse Coding Method to Solve the Similarity Preservation Problem in Image Super-resolution Reconstruction
  • A Sparse Coding Method to Solve the Similarity Preservation Problem in Image Super-resolution Reconstruction

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Embodiment

[0068] A sparse coding method to solve the problem of similarity preservation in image super-resolution reconstruction, the realization flow diagram is as follows figure 1 shown, including the following steps:

[0069] A. Training phase

[0070] (1) Randomly extract high-resolution image block X h and the low-resolution image block X l , and the high-resolution image block X h and the low-resolution image block X l Transform to YCBCR space; only for high-resolution image patch X h and the low-resolution image block X l The brightness information of the next processing; high-resolution image block X h part of Figure 2a As shown, the low-resolution image block X l part of Figure 2b shown;

[0071] (2) Use the Laplacian sparse coding method to train the joint dictionary to obtain a high-resolution dictionary U h and the low-resolution dictionary U l ; high resolution dictionary U h Such as Figure 3a As shown, the low-resolution dictionary U l Such as Figure 3b...

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Abstract

The invention relates to a sparse coding method capable of solving the problem of similarity retention in super-resolution reconstruction of an image. The sparse coding method comprises the following steps of: (1) a training stage: randomly extracting high-resolution image blocks and low-resolution image blocks, and carrying out preprocessing; and training a joint dictionary by using a Laplace sparse coding method so as to obtain a high-resolution dictionary and a low-resolution dictionary; and (2) a testing stage: reading a test image set, loading the high-resolution dictionary and the low-resolution dictionary, processing test image blocks and reconstructing high-resolution image blocks; finding an image which is the most similar with a high-resolution image by using a gradient descent method; and outputting a high-resolution image. According to the method disclosed by the invention, instability of sparse coding processing can be reduced, so that a better super-resolution reconstruction effect is achieved.

Description

technical field [0001] The invention relates to a sparse coding method for solving the problem of similarity preservation in image super-resolution reconstruction, and belongs to the technical field of image processing. Background technique [0002] Image super-resolution is a very useful research area in image processing, which provides a way to solve the inherent resolution limitations of low-cost imaging sensors (such as mobile phones, monitors, etc.), so that images can be viewed on high-resolution display devices on display. This resolution enhancement technique is also very important in the fields of medical imaging and satellite imaging. [0003] Research on the statistical properties of images shows that image patches (image features) can be represented by sparse linear combinations of properly trained over-complete dictionary elements. Inspired by this idea, the sparse coding method used in image super-resolution processing first performs sparse representation for...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T9/00G06T3/40
CPCG06T3/4053G06T9/00
Inventor 江铭炎孙舒琬闫蕾芳郭宝峰
Owner SHANDONG UNIV
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