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Noise elimination method for impact noise image

A technology that impacts noise and images. It is applied in image enhancement, image data processing, instruments, etc., and can solve problems such as reducing image signal-to-noise ratio and image blur.

Active Publication Date: 2016-06-08
DALIAN UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, this kind of selective filtering method based on the median, mean, and extremum (maximum or minimum) in the local window, when performing high-density salt and pepper noise image restoration, the larger filtering window is likely to blur the image, thereby reducing the Image SNR after restoration

Method used

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  • Noise elimination method for impact noise image

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0089] This embodiment is used to compare and illustrate the effect of the image grid processing adopted in the present invention. To this end, two comparative experiments were set up: Experiment 1 without gridding processing, and Experiment 2 with gridding processing, and the image noise density in the experiment was set to 99%.

[0090] 1) In Experiment 1, set the grid size s=512, a=0, which is equivalent to not performing grid processing, and the experimental results are as follows image 3 shown. It can be seen from the experimental results that choosing the least squares filter SLSF effectively repairs the salt and pepper noise pollution pixels, but the processing time is 220 seconds.

[0091] 2) In Experiment 2, set grid size s=256, a=0, the experimental results are as follows Figure 4 As shown, the processing time was reduced to 40 seconds, from Figure 4 As a result, it can be seen that compared image 3 There is no obvious difference in the results of Experiment ...

Embodiment 2

[0094] This embodiment is used to illustrate the effect of using different grid sizes s for different noise pollution densities in the present invention. Four experiments were carried out, namely experiments 3-6.

[0095] Experiment 3: The noise pollution density is 99%, the image block size is a multiple of 16*16, the smallest image block is 16*16, and the largest is 512*512. The relationship between image grid size s and denoising image quality PSNR is as follows: Figure 5 As shown, where the ordinate is PSNR, and the abscissa is the image grid size s. The experimental results show that when the noise density is 99%, when the image grid size is 32, the PSNR reaches a high value. Before the image block is 176, the PSNR of the image changes significantly, and after exceeding 176, the change is relatively slow .

[0096] Experiment 4: The noise pollution density is 95%, the image block size is a multiple of 8*8, the smallest image block is 8*8, and the largest is 232*232. ...

Embodiment 3

[0101] This embodiment is used to illustrate the effect of using the extended image block to eliminate the block effect of the denoising image.

[0102] Experiment 7: The noise density is 90%, the image grid size s=40, a=0, the experimental results are as follows Figure 9 As shown, it can be seen that there are obvious block effects in the denoising results.

[0103] Experiment 8: The noise density is 90%, the image grid size s=40, a=2, the experimental results are as follows Figure 10 shown, it can be seen Figure 9 The blocking effect phenomenon in the system has been well suppressed.

[0104] Experiment 9:

[0105] Taking the Lena image as an example, the simulation test is carried out, and the comparison and analysis results with the existing salt and pepper noise denoising algorithm are as follows: figure 2 shown. exist figure 2 In , the existing algorithm and the effect diagram of noise reduction of the algorithm of the present invention under the condition of ...

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Abstract

The invention discloses a noise elimination method for an impact noise image. The method specifically comprises the following steps: establishing a mark matrix F of a noise polluted image I; dividing the image I and the mark matrix F into M*N grids according to impact noise pollution density rho; extracting an image block T<m,n> and a mark block L<m,n>, which are composed of pixels in the (m,n)th grid in the image I and the matrix F respectively; establishing a pollution pixel set E and a non-pollution pixel set P in the image block T<m,n> through traversing elements in the mark block L<m,n>; obtaining a linear predication system parameter Psi; according to the linear predication system parameter Psi and an Euclidean distance matrix De, calculating to obtain a pollution pixel value shown in the specification; carrying out matrix transposition operation on the pollution pixel value shown in the specification to obtain a noise elimination pixel value E; obtaining a noise-eliminated image block T<m,n>; writing the image block T<m,n> back to the image and replacing pixels of the image in the (m,n)th grid; and traversing all the grids in the image I.

Description

technical field [0001] The invention relates to a method for removing impact noise in an image. Involving patent classification number G06 Calculation; Calculation; Counting G06T General image data processing or generation G06T5 / 00 Enhancement or restoration of images, such as building a similar figure from bitmap to bitmap. Background technique [0002] Digital imaging sensors such as CCD or CMOS are widely used in industry, entertainment, civil and other fields. In the actual use process, affected by factors such as manufacturing defects, device aging, and transmission errors, there is impact noise pollution in the obtained imaging images. Impact noise includes: salt and pepper noise and random impact noise. Among them, salt and pepper noise often manifests as constant extremely bright or extremely dark pixels. Taking a grayscale image with a value range of 0-255 as an example, the value of salt and pepper noise pixels is usually 255 or 0. Such as figure 1 As shown, a i...

Claims

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Application Information

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IPC IPC(8): G06T5/00
CPCG06T5/70
Inventor 刘文龙王阳王心怡
Owner DALIAN UNIV OF TECH
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