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Image super-resolution method based on SAE dictionary learning and neighborhood regression

A dictionary learning and super-resolution technology, applied in neural learning methods, image data processing, graphics and image conversion, etc., can solve problems such as long reconstruction time and obvious block effect

Active Publication Date: 2020-10-27
XIAMEN UNIV TAN KAH KEE COLLEGE
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  • Abstract
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  • Claims
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Problems solved by technology

The algorithm can obtain sufficient prior knowledge and has good subjective visual effects, but the block effect is more obvious, and the reconstruction effect has a great dependence on the learned dictionary, and the reconstruction takes a long time

Method used

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  • Image super-resolution method based on SAE dictionary learning and neighborhood regression
  • Image super-resolution method based on SAE dictionary learning and neighborhood regression
  • Image super-resolution method based on SAE dictionary learning and neighborhood regression

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Embodiment Construction

[0045] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0046] It should be pointed out that the following detailed description is exemplary and is intended to provide further explanation to the present application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0047] It should be noted that the terminology used here is only for describing specific implementations, and is not intended to limit the exemplary implementations according to the present application. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should also be understood that when the terms "comprising" and / or "comprising" are used in this specification, they mean There are features, steps, operations, means, components and / or combina...

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Abstract

The invention relates to an image super-resolution method based on SAE dictionary learning and neighborhood regression, and the method comprises the steps: firstly preparing input data for a dictionary learning model SAE, and carrying out the construction and training of a dictionary; solving a projection matrix by combining a neighborhood regression theory and a dictionary; and finally, performing image reconstruction based on the projection matrix to obtain a high-resolution image. On one hand, the feature expression capability of the dictionary is improved, and the dependence of a reconstruction result on the dictionary is reduced; on the other hand, the neighborhood regression theory is fused, and the reconstruction speed is increased.

Description

technical field [0001] The invention relates to the field of image super-resolution method design, in particular to an image super-resolution method based on SAE dictionary learning and neighborhood regression. Background technique [0002] In reality, due to the limitations of image acquisition equipment, scene changes, and light sources, it is often impossible to obtain high-quality images. When the resolution of the image is low, it cannot meet the requirements of practical applications. The image super-resolution (Super-Resolution, SR) method uses image signal processing technology to reconstruct the existing single or multiple low-resolution (Low Resolution, LR) images into high-resolution (High Resolution, HR) images. It is to add certain additional information in the reconstruction process to make up for the loss of detail information in the process of image degradation. Because SR reconstruction can break through the limitation of the inherent resolution of the imag...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T3/40G06K9/62G06N3/04G06N3/08
CPCG06T3/4053G06N3/08G06N3/045G06F18/28G06F18/2135
Inventor 黄炜钦郭一晶陈俊仁
Owner XIAMEN UNIV TAN KAH KEE COLLEGE
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