Image data processing method

A processing method and image data technology, applied in the field of image processing, can solve the problems of not being able to preserve image edge details, ignoring image prior information, etc., to achieve the effect of preserving edges, satisfying visual effects, and removing noise

Active Publication Date: 2017-03-15
SOUTHWEAT UNIV OF SCI & TECH
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AI Technical Summary

Problems solved by technology

Although NNM has been widely used for low-rank matrix approximation, it still has some problems. In order to ensure the convexity, the prior information of the image is ignored, and the edge details of the image cannot be preserved.

Method used

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Embodiment approach

[0055] As an implementation, the regularization iteration formula of the regularization iteration processing is in, the y (0) =y, y is an overlay matrix formed by overlaying the first denoising image matrix and the filtered residual image matrix, and δ is an iteration step parameter.

[0056] Among them, the number of iterations set by k is 6, 8, 9, and 11 according to the value of the noise equation.

[0057] When the iteration step parameter δ=0.1, when the noise variance value is less than or equal to 40, the soft threshold adjustment factor λ is 0.56, and when the noise variance value is greater than 40, the soft threshold adjustment factor λ is 0.58.

[0058] Step S470, performing singular value decomposition on each of the similarity matrices to obtain a first matrix, a singular value diagonal matrix and a second matrix corresponding to each of the similarity matrices.

[0059] Assuming that the similarity matrix yi is an m×n order matrix, then there is a decomposit...

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Abstract

The embodiment of the present invention provides an image data processing method. The method comprises the steps of subjecting a noise image matrix to total variation so as to obtain a first de-noised image matrix; according to the first de-noised image matrix and the noise image matrix, acquiring a residual image matrix; subjecting the residual image matrix to adaptive wiener filtering so as to obtain a filtered residual image matrix; subjecting the first de-noised image matrix, the filtered residual image matrix and a weight vector to secondary de-noising treatment according to a first preset rule so as to obtain a second de-noised image matrix. The above method fully utilizes the prior information of an image. In this way, the noise is removed, while the edge and the details of the image are better retained at the same time. A high signal-to-noise ratio is obtained, while the structural similarity is also kept at a high level at the same time. Therefore, the visual effect of people can be fully met.

Description

technical field [0001] The present invention relates to the technical field of image processing, in particular to an image data processing method. Background technique [0002] In the process of acquiring, transmitting and storing image signals, it is inevitable to be disturbed by noise, which will cause the information of the image to be submerged and seriously affect the visual quality of the image. A large number of image edges and details are submerged, which brings great difficulties to image analysis and subsequent processing. Elimination of image noise is an important research content in image preprocessing. It provides a good foundation for subsequent processing such as edge detection, image segmentation, feature extraction and pattern recognition. Therefore, how to effectively remove noise while maintaining the clarity of image details and image contrast has become a research hotspot. [0003] With the introduction of the non-local idea, people began to shift fro...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00G06T5/50
CPCG06T5/50G06T5/70
Inventor 路锦正朱豪
Owner SOUTHWEAT UNIV OF SCI & TECH
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