Medical image de-noising method based on optimized nonlocal mean value

A non-local average and medical image technology, applied in the field of image processing, can solve the problems of low algorithm efficiency and large amount of calculation, and achieve the effect of improving effectiveness, good detail contrast, and retaining detail contrast

Inactive Publication Date: 2017-08-08
卡本(深圳)医疗科技有限公司
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Problems solved by technology

However, since the original idea of ​​the non-local mean is to search for the entire image when calculating a pixel, the amount of calculation is large and the algorithm efficiency is low

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  • Medical image de-noising method based on optimized nonlocal mean value
  • Medical image de-noising method based on optimized nonlocal mean value
  • Medical image de-noising method based on optimized nonlocal mean value

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[0038] Preferred embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although preferred embodiments of the invention are shown in the drawings, it should be understood that the invention may be embodied in various forms and should not be limited to the embodiments set forth herein.

[0039] A non-local mean medical image denoising method based on optimization, it comprises the following steps:

[0040] Step 1. For the image to be processed, determine the neighborhood search range and search parameters;

[0041] Step 2. Calculate the similarity between all pixels in the neighborhood of the current pixel and the current pixel to obtain a neighborhood Gaussian weight matrix;

[0042] Step 3. Calculate the filtering result of the current pixel according to the neighborhood Gaussian weight matrix, and limit the filtering result to be within the effective image range;

[0043] Step 4: Repeat step 2 and step 3 to ...

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Abstract

A medical image de-noising method based on an optimized nonlocal mean value comprises the following steps of: 1, determining a neighborhood search range and a search parameter for an image to be processed; 2, calculating the similarity between all pixels in the neighborhood range of a current pixel and the current pixel to obtain a neighborhood Gaussian weight matrix; 3, calculating the filtering result of the current pixel according to the neighborhood Gaussian weight matrix, and defining the filtering result in an effective image range; and 4, repeating the steps 2 and 3, completing the traversal of the entire image, and obtaining and outputting a de-noised result image. The image de-noising method establishes an effective calculation boundary condition, and improves the effectiveness of the parameter. A de-noising core algorithm smoothens various artifacts and noise produced by hardware and software of the medical image, and has effective and good detail contrast.

Description

technical field [0001] The invention is an image processing method. Specifically, an optimized non-local mean based method for medical image denoising. Background technique [0002] Image denoising is the first step in the chain of image processing, the purpose is to improve a given image and solve the problem of image quality degradation caused by noise interference in actual images. Denoising technology can effectively improve the image quality, increase the signal-to-noise ratio, and better reflect the information carried by the original image, which is an important preprocessing method. At present, there are dozens of widely used denoising methods according to the classification of noise generation, frequency spectrum, and signal-to-noise relationship. [0003] Among them, the non-local mean method overcomes the shortcoming that the local mean blurs the detailed information, and effectively preserves the details. On the basis of the non-local mean method, we added the...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00G06T7/00
CPCG06T5/002G06T7/0012
Inventor 王晓芳
Owner 卡本(深圳)医疗科技有限公司
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