Classification of sets of mixed pixels with the hypothesis-testing Hough transform

A new method is presented for mixed pixel classification where the classification of groups of mixed pixels is achieved by using the hypothesis-testing Hough transform. The motivation of the work is that some other estimation methods based on robust statistics, such as the standard Hough transform, have been criticised that, although they can cope with the presence of outliers, they give poor performance in the absence of outliers in comparison to the least-squares-error method. The method proposed in the paper is demonstrated using simulated data and proved to perform equally well in the presence and in the absence of outliers. It is also applied to real Landsat TM data