Descriptor correlation analysis for remote sensing image multi-scale classification

This paper addresses the problem of remote sensing image multi-scale classification by: (i) showing that using multiple scales does improve classification results, but not all scales have the same importance; (ii) showing that image descriptors do not offer the same contribution at all scales, as commonly thought, and some of them are very correlated; (iii) introducing a simple approach to automatically select segmentation scales, descriptors, and classifiers based on correlation and accuracy analysis.