Visual noise reduction processing method based on regular graph Laplace transform

A technology of noise reduction processing and Laplacian matrix, applied in the field of image processing, can solve the problem of complex image noise analysis

Inactive Publication Date: 2019-10-22
陈泰杉
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

The electrical system and external influences in these processes will make the accurate analysis of image noise very complicated

Method used

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  • Visual noise reduction processing method based on regular graph Laplace transform
  • Visual noise reduction processing method based on regular graph Laplace transform
  • Visual noise reduction processing method based on regular graph Laplace transform

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Embodiment Construction

[0032] The present invention will be further described in detail below in conjunction with the accompanying drawings.

[0033] Such as figure 1 As shown, a visual denoising processing method based on regular graph Laplace transform includes the following steps:

[0034] S1. Obtain an image to be processed;

[0035] S2. Sampling the image to be processed to obtain a plurality of image blocks to be processed, and constructing a matrix of image blocks to be processed;

[0036] S3. Constructing a Laplacian matrix corresponding to the image block matrix to be processed;

[0037] S4. Constructing a regular graph sparse coding noise reduction model based on the Laplacian matrix;

[0038] S5. Updating the dictionary and sparse coefficients in the regular graph sparse coding noise reduction model;

[0039] S6. Process the image block matrix to be processed based on the updated regular graph sparse coding denoising model to obtain a denoising image block matrix;

[0040] S7. Overla...

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Abstract

The invention discloses a visual noise reduction processing method based on regular graph Laplace transform. According to the method, a graph regularization sparse coding method is introduced. The feature vector of the Laplacian graph capable of representing the overall structure information of the image is further utilized and participates in the sparse coding process of the image block. A new sparse coding model based on the feature vector of the Laplacian graph is constructed. Therefore noise reduction of the image is achieved.

Description

technical field [0001] The invention relates to the field of image processing, in particular to a visual noise reduction processing method based on regular graph Laplace transform. Background technique [0002] In visual images, image noise refers to unnecessary or redundant interference information existing in image data. The existence of noise seriously affects the quality of remote sensing images, so it must be corrected before image enhancement and classification. Various factors in the image that hinder people from accepting its information can be called image noise. Noise can be defined theoretically as "random error that is unpredictable and can only be understood by the method of probability and statistics". Therefore, it is appropriate to regard image noise as a multidimensional random process, so the method of describing noise can completely borrow the description of random process, that is, use its probability distribution function and probability density distri...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00
CPCG06T5/002
Inventor 陈泰杉
Owner 陈泰杉
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