结合分割和改进SIFT的不同波段SAR图像配准  

Image Segmentation and Improved SIFT for SAR Image Registration of Different Bands

作　　者：王延钊 李彬[3] 崔剑 占必超 WANG Yan-zhao;LI Bin;CUI Jlan;ZHAN Bi-chao(Beijing Institute of Remote Sensing Equipment, Beijing 100854, China;Rocket Force University of Engineering, Elementary Command College, Shaanxi Xi＇ an 710025, China;PLA, No. 31001 Troop, Beijing 100094, China)

机构地区：[1]北京遥感设备研究所 [2]火箭军工程大学初级指挥学院 [3]中国人民解放军31001部队

出　　处：《现代防御技术》2018年第3期41-47,共7页Modern Defence Technology

摘　　要：针对不同波段SAR图像配准问题,提出一种结合阈值分割和改进SIFT描述子的配准方法。该方法首先基于改进的二维交叉熵进行图像分割,通过形态学处理获得图像的稳定区域;然后利用Sobel算子改进特征点梯度幅值和方向的计算,并通过优化的梯度位置方向直方图(GLOH)特征生成新的关键点描述子;最后采用距离比和快速抽样一致(FSC)算法获得最佳匹配点对,完成图像配准。实验结果表明,该方法在提升算法效率的同时,可以获得较高的配准精度。An accurate registration method on the basis of threshold segmentation and optimized scale-invariant feature transform（ SIFT） feature descriptor is proposed for synthetic aperture radar（ SAR） images with different bands. Improved 2 D cross entropy is adopted for image segmentation,and stable regions are detected with morphological processing. Sobel operator is adopted to compute the gradient magnitudes and orientations of SIFT feature points detected in stable regions. The gradient location orientation hologram（ GLOH） is optimized for a more practical use in extraction of a new feature descriptor. The distance ratio and fast sample consensus（ FSC） algorithm are introduced to obtain the best match result. Experimental results show that the proposed method can improve the efficiency of the algorithm while achieving high registration accuracy.

关 键 词：图像配准 尺度不变特征 二维交叉熵 阈值分割 梯度位置方向直方图 快速抽样一致 

分 类 号：TP751.1[自动化与计算机技术—检测技术与自动化装置]