声纳图像的多尺度MAP消斑

A. Isar, D. Isar, S. Moga, J. Augustin, X. Lurton
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引用次数: 12

摘要

由于散射现象的相干性,声纳图像受到称为散斑的倍增噪声的干扰。使用斑点减少过滤器是必要的,以优化图像开发程序。本文提出了一种基于贝叶斯算法的小波域散斑减少方法,该方法在减少散斑的同时,保留了场景的结构特征(如不连续点)和纹理信息。本文提出了一种基于一种新的彩色滤波器变体的对数据进行非线性处理的盲点抑制方法。最后,通过仿真实例验证了该去噪方法的有效性。这些性能与应用最先进的散斑减少技术获得的结果进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-scale MAP despeckling of sonar images
The sonar images are perturbed by a multiplicative noise called speckle, due to the coherent nature of the scattering phenomenon. The use of speckle reduction filters is necessary to optimize the images exploitation procedures. This paper presents a new speckle reduction method in the wavelets domain using a novel Bayesian-based algorithm, which tends to reduce the speckle, preserving the structural features (like the discontinuities) and textural information of the scene. A blind speckle-suppression method that performs a nonlinear operation on the data, based on a new bishrink filter variant is obtained. Finally, some simulation examples prove the performances of the proposed denoising method. These performances are compared with the results obtained applying state-of-the-art speckle reduction techniques.
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