一种基于新型符号函数的小波阈值图像去噪算法

doi:10.11959/j.issn.1000-0801.2017012

Abstract

Abstract:

Based on the existing threshold denoising algorithm,a threshold denoising algorithm based on the new symbolic function was proposed.The new threshold function has advantages of continuous guidance,small deviation of wavelet coefficient,strong threshold adaptability and so on.It not only preserved the low-frequency wavelet coefficients,but also filtered the noise coefficients in the high-frequency coefficients effectively,so that the reconstructed image was closer to the original image.The simulation results of Bridge image,Lena image and B-mode Fetus image with Gaussian white noise show that the visual effect of both the new threshold function and the quantitative indicators PSNR and MSE are better than the existing threshold image denoising algorithm.The edge and detail information can be better protected,have no obvious oscillation,the image is smoother and even,and the method has good stubbornness under the background of complex noise.

Key words: sign function, wavelet threshold, denoising, robustness

CLC Number:

TP391.4

Jinge CUI,Bingquan CHEN,Qing XU,Bo DENG. A wavelet threshold image denoising algorithm based on a new kind of sign function[J]. Telecommunications Science, 2017, 33(1): 45-52.

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References 19

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去噪方法		Bridge			Lena			Fetus		结论
去噪方法	MSE		PSNR/dB	MSE		PSNR/dB	MSE		PSNR/dB	结论
硬阈值法	62.164 2		30.483 2	161.592 1		26.146 5	11.887 9		36.235 6	局部有振荡
软阈值法	77.923 5		29.110 1	220.769 7		25.384 2	25.870 3		35.032 8	边缘出现模糊
参考文献[4]方法	61.739 8		30.314 5	157.227 0		26.139 9	12.159 8		37.412 0	局部过于平滑
参考文献[9]方法	67.772 1		29.923 3	177.684 2		25.723 1	17.247 8		36.221 5	部分细节信息缺失
参考文献[11]方法	62.499 2		30.203 6	158.771 2		26.112 5	15.113 0		36.645 8	景深突变处出现失真
本文方法	52.423 6		30.978 4	136.002 1		26.849 5	8.547 9		38.993 1	效果较好

k		Bridge			Lena			Fetus
k	MSE		PSNR/dB	MSE		PSNR/dB	MSE		PSNR/dB
0	61.873 2		30.446 5	160.851 7		26.223 6	15.012 2		36.597 0
1	52.423 6		30.978 4	136.002 1		26.849 5	8.547 9		38.993 1
2	55.001 5		30.932 7	136.855 3		26.861 0	9.230 4		38.777 6
3	56.328 9		30.749 0	138.130 6		26.728 4	9.603 1		38.289 9

A wavelet threshold image denoising algorithm based on a new kind of sign function

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