Salt and pepper noise filtering method based on similar function with better self-adaptation, denoising and detail protection capabilities

A similarity function and adaptive weighting technology, applied in image data processing, instrumentation, computing, etc., can solve the problem of losing image details and edges

Inactive Publication Date: 2014-11-26
ZHEJIANG UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The traditional method of dealing with salt and pepper noise uses image-related parameters to detect and eliminate noise,

Method used

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  • Salt and pepper noise filtering method based on similar function with better self-adaptation, denoising and detail protection capabilities
  • Salt and pepper noise filtering method based on similar function with better self-adaptation, denoising and detail protection capabilities
  • Salt and pepper noise filtering method based on similar function with better self-adaptation, denoising and detail protection capabilities

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Embodiment Construction

[0039] The present invention will be described in further detail below in conjunction with the accompanying drawings and specific embodiments.

[0040] The method of the present invention comprises the following steps: the image polluted by salt and pepper noise is X, the image after filtering is Z, and the image X polluted by salt and pepper noise is filtered according to the following steps:

[0041] 1) if figure 1 As shown, in the 8-bit grayscale image, the filter window size of the image X polluted by salt and pepper noise is 3×3, if the central pixel grayscale value x(i,j) of the filter window is 0 or 255, i,j are the abscissa and ordinate of the center pixel of the filter window respectively, then the center pixel of the filter window is a noise pixel or a suspected noise pixel, otherwise it is a signal pixel;

[0042] 2) Establish a marker matrix F with the same size as the image X polluted by salt and pepper noise to mark the noise pixels. In the marker matrix F, if t...

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Abstract

The invention discloses a salt and pepper noise filtering method based on a similar function, comprising the steps of setting an image filtering window in a 8-bit gray level image, determining noise pixels or suspected noise pixels through central pixel gray level values, and otherwise, judging the pixels to be signal pixels, establishing a marking matrix to mark the noise pixels, eliminating the pixel points in the filtering window, wherein the gray levels of the pixel points are identical to that of the central pixels, constituting a first signal point set by using the signal points which satisfy the marking matrix elements, processing the signals in the first signal point collection to obtain a first output image, setting the marking matrix element corresponding to the position of the output pixel in the output image to finish the filtering processing. The invention has better capability of denoising and maintaining details.

Description

technical field [0001] The invention relates to a filtering method for removing salt-and-pepper noise from an image, in particular to an adaptive weighted salt-and-pepper noise filtering method based on a similarity function. Background technique [0002] The image is affected by factors such as the external environment and the quality of sensor components during the process of image acquisition, transmission and reception, which introduces different types of noise, resulting in a decrease in image quality, among which salt and pepper noise is one of the common noises. Whether the salt and pepper noise can be effectively removed plays an important role in achieving efficient image segmentation and image feature recognition. The traditional method of processing salt and pepper noise uses image-related parameters to detect and eliminate noise, but while removing noise, it also modifies the gray value of non-noisy pixels, losing the details and edges of the image. Contents of...

Claims

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Application Information

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IPC IPC(8): G06T7/20
Inventor 齐冬莲闫云凤何海明杨捷辛焕海
Owner ZHEJIANG UNIV
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