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基于正余弦分解的自适应全变分散斑去噪方法

Adaptive Total Variation Speckle Denoising Method Based on Sine-Cosine Decomposition

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摘要

为解决相位图在去噪过程中出现的散斑噪声残留和边缘纹理模糊问题,基于正余弦分解提出了一种自适应全变分去噪方法。首先,用正余弦函数将原始相位图分解成两幅相位图;然后用自适应全变分算法处理分解后的相位图;最后,通过反正切运算合成去噪后的相位图,以快速去除大量散斑噪声并保留图像的边缘信息。对去噪结果进行定量评价和分析表明,与其他降噪方法相比,本方法得到的图像峰值信噪比提高了2.0 dB,且结构相似度较高。同时可以自适应地选择参数,减少去噪后相位图的波动性,改善相位图的质量。

Abstract

In order to solve the speckle noise residue and edge texture blur in phase image denoising, an adaptive total variation denoising method based on sine-cosine decomposition is proposed in this work. First, the original phase image is decomposed into two phase images by sine and cosine function. Then, the decomposed phase image is processed by adaptive total variation algorithm. Finally, the denoised phase image is synthesized by arctangent operation to quickly remove a large amount of speckle noise and retain the edge information of the image. The quantitative evaluation and analysis of the denoising results show that, compared with other denoising methods, the peak signal-to-noise ratio of the image obtained by this method is improved by 2.0 dB, and the structure similarity is higher. At the same time, the parameters can be adaptively selected to reduce the fluctuation of the phase image and improve the its quality.

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中图分类号:O436.1; TP391

DOI:10.3788/CJL202047.1004004

所属栏目:测量与计量

基金项目:国家自然基金、装备预研领域基金、国防科技重点实验室基金、山西省自然科学基金、山西省归国留学基金;

收稿日期:2020-04-30

修改稿日期:2020-06-11

网络出版日期:2013-10-01

作者单位    点击查看

刘吉:中北大学电子测试技术重点实验室, 山西 太原 030051中北大学信息与通信工程学院, 山西 太原 030051
黄晓慧:中北大学信息与通信工程学院, 山西 太原 030051
武锦辉:中北大学电子测试技术重点实验室, 山西 太原 030051
苏凝钢:中北大学信息与通信工程学院, 山西 太原 030051
于丽霞:中北大学信息与通信工程学院, 山西 太原 030051

联系人作者:黄晓慧(1095067965@qq.com)

备注:国家自然基金、装备预研领域基金、国防科技重点实验室基金、山西省自然科学基金、山西省归国留学基金;

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引用该论文

Liu Ji,Huang Xiaohui,Wu Jinhui,Su Ninggang,Yu Lixia. Adaptive Total Variation Speckle Denoising Method Based on Sine-Cosine Decomposition[J]. Chinese Journal of Lasers, 2020, 47(10): 1004004

刘吉,黄晓慧,武锦辉,苏凝钢,于丽霞. 基于正余弦分解的自适应全变分散斑去噪方法[J]. 中国激光, 2020, 47(10): 1004004

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