A DCT-based Change Detection Method for Multi-Temporal SAR Images

This paper aims at effectively detecting the changes in multi-temporal synthetic aperture radar (SAR) images. Since pixel-based method does not sufficiently utilize the correlation between pixels, it usually may only be used in some specific applications. We propose a change detection method that is based upon discrete cosine transform (DCT) classification. It can utilize the correlation between pixels and eliminate unimportant or nuisance forms of changes. It generates a threshold automatically in DCT classification according to the relationship between DCT coefficient and pixel's gray level. In order to eliminate the block effect, we check pixels not only within the target block, but also inside the neighborhood window around the target block. Experimental results show that the proposed method outperforms some recently published pixel-based methods.