基于中性集合与双边滤波的NSCT域声呐图像去噪

Sonar Image Denoising in NSCT Domain Based on Neutral Set and Bilateral Filtering

声呐设备在获取水下图像时,由于海底混响、散射回波和设备等因素,会产生严重的斑点噪声干扰,降低图像质量.为了克服这一挑战,提出基于中性集合与双边滤波的非下采样轮廓波变换声呐图像去噪.该方法探索了一种适合处理非下采样轮廓波变换分解的高频子带噪声的聚类去噪方法,将中性集合域作为聚类的方法应用在每一层高频子图像,用真子集、不确定集和假集表示,实现分离噪声,保留有效信息;再使用双边滤波去除真子集中被误认为是图像信息的噪声;对低频系数使用双边滤波进行平滑.最后将处理后的低频子带与高频子带进行NSCT重构,达到从图像中去除斑点噪声的目的.实验表明,本文方法能够提高图像视觉效果,改善图像均方误差、峰值信噪比等评价指标,同时也适用于去除高密度噪声.

Sonar equipment can produce severe speckle noise interference and degrade image quality when acquiring underwater images due to seafloor reverberation,scattered echoes and equipment.To overcome this challenge,a Non-subsampled contourlet transform(NSCT)sonar image denoising based on neutral ensemble with bilateral filtering is proposed.The method explores a clustering denoising method suitable for dealing with high-frequency subband noise of non-subsampled contourlet transform decomposition,where the neutrosophic set domain is applied as clustering to each layer of high-frequency sub-images,represented by true subsets,uncertainty sets and false sets,to achieve separation of noise and retention of valid information;then bilateral filtering is used to remove the noise mistaken as image information in true subsets;bilateral filtering for low-frequency coefficients smoothing is performed using bilateral filtering.Finally,the processed low-frequency subbands and high-frequency subbands are reconstructed by NSCT to achieve the purpose of removing speckle noise from the image.The experiments show that the proposed method can improve the visual effect of the image,improve the evaluation indexes such as mean square error and peak signal-to-noise ratio,and is also suitable for removing high-density noise.