由于成象条件和环境误差的影响,不同传感器获得的遥感图像间存在很大的灰度差异,这使两图象间的配准和信息融合变得十分困难.该文深入研究了不同条件下遥感图像灰度差分布的统计特性,提出了灰度差异的自相关模型.为进一步的灰度差修正奠定了基础.实验结果表明,该自相关模型与从实际样本采样获取的自相关序列是基本一致的.这在信息融合和图象匹配技术领域都具有重要的意义.

There are great gray-level differences between multi-sensor images, which make it very difficult to register them. An auto-correlation model of gray-level difference is described in this paper, which is assumed an ergodic wide-sense stationary two-dimensional random field with zero mean value in a local region. This research will be a powerful support to gray-level difference rectifying of multi-sensor images. Experiment results show the validity of the proposed auto-correlation model.