【摘要】 由不同传感器摄取的遥感影像因成像模式、拍摄角度和分辨率不同,给两者之间的配准造成困难。针对该问题,提出归一化SIFT算法,通过对SIFT描述子归一化的处理,降低不同光学影像色调差异大的影响,并通过与最小二乘法和双线性内插法的结合,完成自动配准。选取角度和尺度偏差较大的SPOT与ASTER影像、ASTER与TM影像2组数据进行实验。结果证明,该算法鲁棒性强,配准精度高。更多还原

【Abstract】 The imaging model,acquired angle and resolution between image acquired by diverse remote sensing sensors are different,which throws difficulty in the registration between them.Aiming at this problem,the normalized SIFT algorithm is proposed in this paper.The SIFT descriptors are normalized,which can reduce the impact of hue difference between image acquired by different sensors,and then combined with least-square equation and bilinear interpolation method,the automatic registration is achieved.Two groups of images,which have big differences in acquired angle and resolution,SPOT and ASTER,ASTER and TM,are tested.Results dedicate that this algorithm is robust and has a high accuracy.更多还原