针对侧扫声呐图像对比度低、噪声强度大特点导致的部分传统滤波方法降噪能力的不足，提出一种基于剪切波变换的侧扫声呐图像降噪方法。首先对侧扫声呐图像进行剪切波变换，在考虑噪声水平的基础上，对剪切系数进行阈值处理，再将修正后的系数进行剪切波逆变换，重构侧扫声呐图像，实现了侧扫声呐图像的降噪。实验结果表明，该方法相比于维纳滤波、小波滤波和非局部均值滤波等常用降噪方法，可以获取更好的图像效果，在侧扫声呐图像降噪中具有综合优势。
In view of the fact that the side-scan sonar image has the characteristics of low contrast and large noise intensity, which led to noise reduction effect of some traditional filter methods is insufficient, a denoising method based on shearlet transform is proposed. First, the side-scan sonar image is divided with shearlet transform. Then, shearlet coefficients are processed by the threshold method considering the noise measrement. Finally, the image is reconstructed through the inverse shearlet transform with the amended coefficients, and the purpose of image denoising is realized. The experiment results show that the method of this paper is suitable for side-scan sonar image processing, obtains better image denoising effect than Wiener filtering, wavelet filtering and non-local means filtering, has comprehensive advantages in side-scan sonar image noise reduction.
2022,44(3): 129-134 收稿日期：2021-06-23
DOI：10.3404/j.issn.1672-7649.2022.03.025
分类号：P229.3
基金项目：国家自然科学基金资助项目(41876103)
作者简介：王磊(1984-)，男，硕士，助理工程师，主要从事海洋测绘和信号处理研究工作
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