基于稀疏表示的水下声纳图像去噪方法

Di Wu, Xue Du, Kaiyu Wang
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引用次数: 20

摘要

为了更有效地去除声纳图像中复杂而严重的噪声,本文提出了一种基于稀疏表示的图像去噪方法。利用OMP对声纳图像在DCT字典上进行分解和重构,是去除加性噪声的有效方法。然后对重构图像进行对数变换,使其适应稀疏表示去噪模型。实验证明了该方法的有效性。结果表明,该方法能够有效地去除声纳图像中的加性和乘性噪声,并且在去噪效果和保留细节方面具有特殊的吸引力。
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An Effective Approach for Underwater Sonar Image Denoising Based on Sparse Representation
In order to remove the complex and severe noise from sonar image more effectively, an image denoising approach based on sparse representation is carried out in this paper. To decompose and then reconstruct the sonar image on DCT dictionary with OMP is effective for additive noise removing. Then a logarithmic transformation was applied on the previous reconstructed image to make it adapt to sparse representation denoising model. Experiments are provided to demonstrate the performance of the proposed approach. Results show that this method is efficient in removing additive and multiplicative noise from the sonar image and is also particularly appealing in terms of both denoising effect and keeping details.
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