摘要
针对现有去噪处理方法获得的舰船尾迹图像质量较差,边缘信息模糊等缺点,提出一种基于MCA与特定滤波器相结合的舰船尾迹图像去噪处理方法,对舰船尾迹成像模型和相干斑噪声模型以及统计特性进行了分析和计算;采用MCA对舰船尾迹结构成分与水面复杂背景纹理成分进行有效分离,分别选择双正小波变换和剪切波变换构建舰船尾迹纹理字典和结构成分字典,将舰船尾迹图像形态成分分离过程转化成最优化问题进行求解,去除了干扰;采用同态滤波对去噪处理后的舰船尾迹图像进行增强,并设计了高通滤波器来替代同态滤波函数中的滤波器,实现了舰船尾迹图像的中低频成分抑制和高频部分增强。实验结果表明,所提方法对舰船尾迹图像的去噪处理效果最好,得到的图像边缘清晰度更高,纹理特征也更加显著,且细节信息得到了增强。
Aiming at the drawbacks of the existing image processing methods such as poor image quality and fuzzy edge information, this paper proposes a method of image denoising based on the combination of MCA and specific filter.And speckle noise model and statistical characteristics were analyzed and calculated. The MCA was used to separate the components of ship wakes and the complex background texture components of the water surface effectively. Two-dimensional wavelet transform and shear wave transformation were used to construct the wake texture dictionary and Structural components dictionary, the ship wake image morphological component separation process into optimization problems to solve, remove the interference; using homomorphic filter to the de-noised ship wake image enhancement, and designed a high-pass filter instead The filter in the homomorphic filter function realizes the low and middle frequency component suppression and the high frequency partial enhancement of the wake image. The experimental results show that the proposed method has the best effect on the image denoising of ship wake. The obtained image has better edge definition and texture features, and the detail information is enhanced.
出处
《舰船科学技术》
北大核心
2018年第1X期28-30,共3页
Ship Science and Technology
基金
河南省教育厅科学技术研究重点资助项目(12B520047)
关键词
舰船尾迹
图像
去噪
处理
ship wake
image
deny noise
deal with
