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Application of multi-resolution analysis in sonar image denoising

机译:多分辨率分析在声纳图像去噪中的应用

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Sonar images have complex background, low contrast, and deteriorative edges; these characteristics make it difficult for researchers to dispose the sonar objects. The multi-resolution analysis represents the signals in different scales efficiently, which is widely used in image processing. Wavelets are successful in disposing point discontinuities in one dimension, but not in two dimensions. The finite Ridgelet transform (FRIT) deals efficiently with the singularity in high dimension. It presents three improved denoising approaches, which are based on FRIT and used in the sonar image disposal technique. By experiment and comparison with traditional methods, these approaches not only suppress the artifacts, but also obtain good effect in edge keeping and SNR of the sonar image denoising.
机译:声纳图像背景复杂,对比度低,边缘变差。这些特征使研究人员难以处置声纳物体。多分辨率分析有效地表示了不同比例的信号,已广泛应用于图像处理中。小波成功地将点不连续性放置在一维中,但不能成功地将其放置在二维中。有限Ridgelet变换(FRIT)有效地处理了高维中的奇点。它提出了三种改进的去噪方法,它们基于FRIT并用于声纳图像处理技术。通过实验和与传统方法的比较,这些方法不仅抑制了伪像,而且在边缘保持和声纳图像降噪的信噪比方面都取得了良好的效果。

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