CAJ | 학술논문

为实现MSTAR图像无监督分割,并提高分割精度和计算效率,提出了一种基于Gabor滤波增强的自适应阈值分割算法.首先利用多尺度、多方向的Gabor滤波器组对待分割图像进行滤波处理,抑制目标、阴影和背景区域内部的斑噪起伏,同时增强区域间的差异性;在此基础上,通过对增强图像统计特性的分析,给出了灰度阈值计算形式,实现了MSTAR图像的自适应分割.实验结果表明,本文算法对不同斑噪强度的MSTAR图像均具有良好的处理效果,在分割精度、计算效率等方面优于传统的OTSU,以及FCM、MRF等分割方法.
위실현MSTAR도상무감독분할,병제고분할정도화계산효솔,제출료일충기우Gabor려파증강적자괄응역치분할산법.수선이용다척도、다방향적Gabor려파기조대대분할도상진행려파처리,억제목표、음영화배경구역내부적반조기복,동시증강구역간적차이성;재차기출상,통과대증강도상통계특성적분석,급출료회도역치계산형식,실현료MSTAR도상적자괄응분할.실험결과표명,본문산법대불동반조강도적MSTAR도상균구유량호적처리효과,재분할정도、계산효솔등방면우우전통적OTSU,이급FCM、MRF등분할방법.
Image segmentation is a hot point in the research field of automatic target recognition of SAR image. In order to segment the MSTAR image automatically, a new adaptive method is proposed. Firstly, 2D Gabor filters with various orientations and scales are used to enhance the original image, which can effectually reduce speckle noise in the background, and smooth the interior of the homogeneous regions. Then the analysis of the statistical characteristics of the enhanced image is made, based on which the adaptive thresholding rules is presented for the automatically segmentation of the images. Experiment results with the MSTAR images indicate that the algorithm presented has advantage of segmentation accuracy, calculation efficiency and noise robustness over the traditional methods, such as OTSU, FCM and MRF.