基于正交变换的多通道遥感影像变化检测

针对多时相多通道遥感影像的变化检测问题，引入了多元统计中的典型相关分析方法，对遥感影像进行典型变换，并采用最小噪声比率变换对典型变换结果作后处理，得到差异影像，初步解决了将变化信息集中到少数分量中的问题。实验证实了该方法的有效性，并与主成分分析方法进行了比较。

Multi-Channel Remote Sensing Imagery Change Detection Based on Orthogonal Transformations

An approach based on canonical correlation analysis in multivariate statistics is introduced to change detection of multi-temporal/multi-channel remote sensing imagery. The basic idea is to take multichannel remote sensing imageries acquired at different times as groups of random multivariates, then construct linear combinations to explore correlations between them, thus finding out biggest differences over the time span. In our approach, MAD transformation is firstly conducted on original imageries to produce a difference image, then MNF transformation is utilized as a postprocessing step to separate noise from signal in difference images, and change information can be effectively concentrated into a few components of the final result. Another change detection method based on PCA is also described briefly for comparison. Experimental results of a case study using Landsat5 TM imageries are presented to demonstrate the effectiveness of our method. And the characteristics of correlation between results and original imageries are discussed in detail.