CAJ | 학술논문

该文基于非下采样Contourlet变换(NSCT)和SAR图像的统计特性,提出一种SAR图像增强方法,给出一种基于非下采样塔型分解的斑点噪声方差估计算法和一种基于方向邻域模型的弱边缘增强算法.该文在不同方向子代进行斑点方差估计,利用局部方向统计信息对NSCT系数并进行强边缘、弱边缘和噪声分类并进行弱边缘的增强和噪声的抑制.实验结果表明,该方法在方向信息保留和斑点抑制上优于非下采样小波变换(NSWT)相应方法.
해문기우비하채양Contourlet변환(NSCT)화SAR도상적통계특성,제출일충SAR도상증강방법,급출일충기우비하채양탑형분해적반점조성방차고계산법화일충기우방향린역모형적약변연증강산법.해문재불동방향자대진행반점방차고계,이용국부방향통계신식대NSCT계수병진행강변연、약변연화조성분류병진행약변연적증강화조성적억제.실험결과표명,해방법재방향신식보류화반점억제상우우비하채양소파변환(NSWT)상응방법.
Based on nonsubsampled Contourlet transform and SAR image statistical property, a SAR image enhancement method is proposed. A speckle noise variance estimate algorithm is given using nonsubsampled Laplace Pyramid decompose, and a wake edge enhancement algorithm using directional local neighborhood is proposed. This paper estimate the speckle variance in each decomposes direction, and the directional local neighborhood statistical is used to distinguish the strong edge, wake edge and noise. The wake edge is enhanced and the speckled noise is restrained. Experiment results show that the method represents better performance compared with NSWT in wake edges information enhancement and speckle reduction.