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Fast realization method for digital image non-local average denoising

A non-local averaging, digital image technology, applied in image enhancement, image data processing, instruments, etc., can solve the problem of non-local averaging filtering algorithm taking a long time, and achieve the effect of reducing computational complexity and improving real-time performance.

Inactive Publication Date: 2017-08-22
XI'AN POLYTECHNIC UNIVERSITY
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Problems solved by technology

[0005] The purpose of the present invention is to provide a fast implementation method for non-local average denoising of digital images, so as to improve the time-consuming problem of non-local average filtering algorithm

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  • Fast realization method for digital image non-local average denoising
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  • Fast realization method for digital image non-local average denoising

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Embodiment Construction

[0042] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0043] The present invention is a fast implementation method of non-local average denoising of digital image, which utilizes the basis of fast matrix processing speed of matlab software to put non-local pixels into a large matrix for simultaneous processing, thereby achieving the purpose of saving time. like figure 1 As shown, during the execution of the NLM algorithm of the present invention, the size of two windows is fixed, the first is the pixel similarity window equal to 7×7, and the second is the window of the pixel neighborhood window search range is equal to 21×21, namely In the 21×21 size search window, the NLM algorithm is run with a pixel similarity window scale of 7×7. The 7×7 window slides in the 21×21 area range, and finally the center pixel of the area is measured by the similarity of each area. The assigned grayscale weight. ...

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Abstract

The invention discloses a fast realization method for digital image non-local average denoising. The fast realization method specifically comprises the steps of: 1) selecting an appropriate searching window and similar windows, and determining a radius M of the searching window and a radius R of the similar windows; 2) performing boundary extension on an image according to the radii of the searching window and the similar windows as well as the size of R+M; 3) forming a large matrix A and large matrix B, wherein the matrix A stores results of the similar windows searching within the searching window, and the similar window in which a current central pixel locates is extended to form the matrix B according to the size of the matrix A; 4) estimating weights of the large matrixes, calculating the matrix A and the matrix B to determine similarity of the similar windows according to Euclidean distance, and further determining a weight allocated to a current pixel; 5) and performing weighted averaging on the large matrixes, and performing weighted averaging on the calculated weights to obtain a final estimation result of the current pixel. By adopting the fast realization method image non-local average denoising can be realized quickly, and the program operation time is greatly saved.

Description

technical field [0001] The invention belongs to the field of digital image noise suppression, and relates to a fast implementation method for digital image non-local average denoising. Background technique [0002] Digital image processing, also known as computer image processing, is a process of converting image signals into digital signals and processing them with the help of computers. With the advancement of science and technology and the continuous in-depth exploration of nature by human beings, the application of digital image processing is becoming wider and wider. From the initial communication, aerospace, military, biomedicine, to the industrial production that benefits the people, public security criminal investigation and robot vision, video and multimedia systems, etc. [0003] Image denoising has always been a hot topic in image preprocessing. It is a goal that people have been pursuing to find a method that can effectively reduce noise and preserve image edge...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00
CPCG06T5/70
Inventor 朱磊蔡飞飞潘杨郭林源
Owner XI'AN POLYTECHNIC UNIVERSITY
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