Impulse Noise Suppression of Image Based on Iterative Nonlocal Mean

A non-local average and image technology, applied in image enhancement, image data processing, instruments, etc., can solve the problems of image accuracy and precision degradation, loss of image detail information, excessive smoothing, etc., to improve the restoration quality and effectively remove pulses noise effect

Inactive Publication Date: 2016-11-02
XIDIAN UNIV
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

[0004] First, these two methods regard the edge and detail pixels of the image as noise points in the filtering process, resulting in excessive smoothing and loss of image detail information.
[0005] Second, when the noise density increases, the accuracy and precision of the image restored by these two methods will drop sharply, which cannot meet the visual requirements of the human eye and the processing requirements of the computer.

Method used

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  • Impulse Noise Suppression of Image Based on Iterative Nonlocal Mean
  • Impulse Noise Suppression of Image Based on Iterative Nonlocal Mean
  • Impulse Noise Suppression of Image Based on Iterative Nonlocal Mean

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Embodiment Construction

[0044] Embodiments of the present invention will be described in further detail below in conjunction with the accompanying drawings.

[0045] refer to figure 1 , the implementation steps of the present invention are as follows:

[0046] Step 1, use the histogram method for noise detection on the impulsive noise image I to be processed.

[0047] (1.1) count the number of pixels corresponding to each grayscale value of the noise image I, and draw the histogram H of the impulse noise image I according to the number counted;

[0048] (1.2) Take the extreme points at both ends of the envelope function of the histogram H as the minimum threshold T min and the maximum threshold T max ;

[0049] (1.3) Compare the gray value I(i, j) of the pixel in the noise image I with the two thresholds T min , T max Comparison: if I(i,j)≤T min , or I(i,j)≥T max , then this pixel is considered to be a pixel polluted by noise, if T min max , then this pixel is considered to be a pixel not po...

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Abstract

The invention discloses a method for suppressing image impulse noise based on an iterative non-local mean value, which is mainly used to solve the problems that the existing method cannot preserve image detail information in the denoising process and cannot restore a clear image under high noise density. The implementation steps are: (1) use the histogram method to detect the noise position on the noise image; (2) pre-filter the noise image by selecting and switching the median filter; (3) use iterative non-local filtering on the pre-filtered image The average method is used to obtain a clear image that effectively suppresses impulse noise. Simulation experiments show that the present invention is superior to existing algorithms in subjective visual effects and objective evaluation results under the condition of different degrees of impulse noise, and can be used to suppress high-density impulse noise and restore clear images.

Description

technical field [0001] The invention belongs to the technical field of digital image processing, and in particular relates to a method for suppressing image pulse noise, which can be used to restore clear images from noise images polluted by high-density pulse noise. Background technique [0002] Impulse noise is composed of discontinuous, irregular pulses or noise spikes of short duration and large amplitude. Impulse noise can be generated by many factors, such as electromagnetic interference, faulty defects in communication systems, state changes of electrical switches and relays in communication systems, etc. In digital image processing, such as in the process of acquisition and transmission, the image cannot avoid the interference of impulse noise. Impulse noise causes random distribution of black and white noise points in the image, which greatly reduces the image quality and leads to subsequent transmission and A serious error occurred during processing. For example,...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00
Inventor 王晓甜王艳涛石光明季超亚张佩钰吴金建刘丹华林杰
Owner XIDIAN UNIV
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