Change detection in heterogeneous remote sensing images based on the fusion of pixel transformation

Zhun-ga Liu, Li Zhang, Gang Li, You He

Abstract: A new change detection method for heterogeneous remote sensing images (i.e. SAR & optics) has been proposed via pixel transformation. It is difficult to directly compare the pixels from heterogeneous images for detecting changes. We propose to transfer the pixels in different images to a common feature space for convenience of comparison. For each pixel in the 1 st image, it will be transferred to the 2 nd feature space associated with the 2 nd image according to the given unchanged pixel pairs. In fact, this transformation is done assuming that the pixel is not affected by the events. Then the difference value between the estimation of transferred pixel and the actual one in the same location of the 2 nd image can be calculated. The bigger difference value, the higher possibility of change happening. We can similarly do the opposite transformation from the 2 nd image to the 1 st image, and one more difference value is obtained in the 1 st feature space. Change occurrences will be detected using Fuzzy C-means clustering method based on the sum of two difference values. The flood detection in the SAR and optical images is given in the experiments, and it shows that the proposed method is able to efficiently detect changes.