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Circular self-adaptation template based image weighted mean filtering method

A technique of weighted mean filtering and self-adaptive template, applied in the field of image processing, can solve the problem of not giving full play to the role of grayscale information and distance information, and achieve the effect of reducing loss and improving filtering effect.

Inactive Publication Date: 2013-08-14
HEBEI NORMAL UNIV
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AI Technical Summary

Problems solved by technology

[0007] Although the use of n * n square template filtering utilizes the gray information of most of the pixels around the current pixel, it does not fully utilize the role of all the gray information and distance information in the neighborhood of the current pixel in filtering.

Method used

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  • Circular self-adaptation template based image weighted mean filtering method
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  • Circular self-adaptation template based image weighted mean filtering method

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Embodiment Construction

[0074] The concrete steps of this embodiment are as follows:

[0075] (1) Read in a frame of image, let the first pixel be the current pixel;

[0076] (2) Determine whether the current pixel is a noise point:

[0077] The method of judging the noise point is the threshold interval method, that is, the pixel point whose gray value is between the threshold A and B is a signal point, otherwise it is a noise point;

[0078] When the current pixel point is a noise point, perform step (3);

[0079] When the current pixel point is a signal point, perform step (2.1);

[0080] (2.1) Set the next pixel as the current pixel, and then return to step (2);

[0081] (3) Set the current pixel template as empty:

[0082] First select the sequence number K in the following distance table to be 1, and set the number N of signal points in the current pixel template to 0;

[0083]

[0084] Note: The above distance table only lists the first 31 items (ie k=31). In fact, the distance table c...

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Abstract

The invention relates to a circular self-adaptation template based image weighted mean filtering method. The technical key points of the method are that a circular template is adopted to carry out the expansion of a self-adaptation template, and noise elimination is carried out by combining and calculating the distance weighting and the normalization weight of signal points relating to calculation. The method has the advantages that firstly, the circular template is used, and contains more valuable information, compared with a traditional square template, so that noise-eliminated images can better approximate to primary images; secondly, the circular template can be adaptively expanded according to the number of signal points in the template, with regard to images polluted by salt and pepper noises with various intensity (1-90 percent), which all obtain a relatively very good filtering effect; and lastly, mean calculation utilizes distance information of image space, and the filtering effect is further improved.

Description

[0001] technical field [0002] The invention relates to an image weighted mean value filtering method based on a circular self-adaptive template, which is particularly suitable for filtering salt and pepper noise in images, and belongs to the technical field of image processing. Background technique [0003] Since most of the information received by humans is obtained from images, images, as the visual basis for humans to perceive the world, are an important means for humans to obtain information, express information, and transmit information. However, in the process of image signal formation and transmission, due to the imperfection of the image acquisition system, transmission medium, and imaging system and the interference of the external environment, noise will be introduced to varying degrees, thereby degrading the quality of the output image. In general, images in reality are noisy images. In many important applications, such as noise pollution of medical images, it ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00
Inventor 张有会王志巍李俊红刘淑娟董蕊赵晔郭晓文吴朋波
Owner HEBEI NORMAL UNIV
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