暗弱目标偏振度图像与偏振角图像去噪方法研究

Research on Denoising Method for Polarization Degree Image and Polarization Angle Image of Dim and Weak Targets

针对暗弱目标偏振融合图像存在背景噪声强、细节轮廓特征不明显等问题,利用偏振度图像中高斯背景噪声灰度与待测目标灰度的差异性,提出了基于噪声模板阈值匹配的偏振度图像去噪算法。分析了偏振角图像中纯噪声区域子图像与目标轮廓区域子图像的灰度相关性,提出了基于区域灰度相关性匹配的偏振角图像去噪算法,与传统去噪方法相比,该算法可有效去除大量背景噪声,更好地保留目标轮廓特征。偏振图像融合对比实验结果进一步证明,提出的偏振图像去噪方法可显著提高暗弱目标在图像中的对比度,改善偏振融合增强图像的质量。

Aiming at the problems of strong background noise and indistinct detail contour features in polarization fusion image of dim and weak targets,considering to the difference of gray level between Gaussian background noise and target contour in degree of polarization image,a denoising algorithm based on noise template threshold matching is proposed.Analyzing the gray correlation between the sub-image of pure noise and the sub-image of target contour in the angle of polarization image,a denoising algorithm based on Region Gray Correlation Matching(RGCM)is proposed,compared with the traditional denoising methods,the RGCM algorithm can effectively remove a large amount of background noise and retain the target contour features better.The experimental results of polarization image fusion further prove that the algorithm proposed in this paper can not only improve the contrast of dim and weak targets but also significantly improve the image quality in polarization fusion enhancement image.