Auto Correlation Model of Multi-Sensor Images

doi:10.11834/jig.20000305

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Auto Correlation Model of Multi-Sensor Images
Vol. 5, Issue 3, Pages: 202(2000)
Published：2000
DOI： 10.11834/jig.20000305
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DOI：

Auto Correlation Model of Multi-Sensor Images[J]. Journal of Image and Graphics, 2000, 5(3): 202. DOI： 10.11834/jig.20000305.

摘要

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.

Abstract

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.