非合作水雷目标图像非均匀强噪声去除方法

水雷目标探测会受到水下非均匀强噪声（有机质、悬浮颗粒等）的干扰，为了解决这一问题，提出了一种新的去噪方法。首先优化局部保边缘滤波算法，提出了基于边缘感知约束的局部保边缘滤波，在模型中引入了一个空间自适应的边缘感知约束正则化项，用来更好地表征图像的边缘及细节，使得算法的保边缘平滑特性更好。其次针对强噪声的非均匀特性，采用多尺度策略，迭代地将优化后的模型运用到每个尺度的去噪结果上生成多尺度分解，并在多尺度分解的过程中，逐步增加去噪尺度，将不同尺度的噪声逐步从上一尺度的去噪结果中分离出来。实验结果表明，相较于其他经典去噪方法，提出的算法能够在更好地去除水下非均匀强噪声的同时保留水雷目标信息，对实时水雷作业有着一定的指导意义。

Non-uniform strong noise removal method for non-cooperative mine target image

The detection of mine targets will be interfered by the underwater non-uniform strong noise(organic matter,suspended particles,etc).To solve this problem,a novel denoising method was proposed.Firstly,the local edge preserving filtering algorithm was optimized and the local edge preserving filtering based on edge perception constraint was proposed.A spatially adaptive edge perception constraint regularization term was introduced into the model to better represent the edges and details of the image,so that the edge-preserving and smoothing property could be better.Secondly,the multi-scale strategy was used to solve the heterogeneity of strong noise,the optimized model was iteratively applied to the noise removal results of each scale to generate multi-scale decomposition,and the denoising scale was gradually increaseed in the process of multi-scale decomposition.The noise of different scales was gradually separated from the denoising results of the previous scale.The experimental results show that,compared with other classical denoising methods,the proposed algorithm can better remove the underwater non-uniform strong noise while retaining the mine target information,which also has a certain guiding significance for real-time mine operation.