Abstract:

The information extraction of the linear features’ edge in the high-resolution remote sensing images has been a problem，which mostly from the contradiction formed by the edge information and noise. The more obvious edge information the stronger the noise will be. In this paper, the high-pass filter and statistical filter are used to build a multi-filter, processing the IKONOS image. Compared with the different processing results of IKONOS images by three different high-pass filters windows, we can choose the best window that make the IKONOS images boundary feature outstanding and reduce the region fuzzy degree. The approximately contour of target scalar can be distinguished. Based on this we processed the IKONOS images by statistical filtering. The images noises decrease significantly and gray distribution more lumped and smoothing. We can find the result which is processed by statistical filtering is better than the result which is only processed by high-pass filtering after the edge detection. The result shows that noise in the filtered image significantly was decreased and the SNR markedly improved. The images processed by statistical filtering could improve the accuracy of detection. It indicates that automatic extract vector information is feasible high-resolution remote sensing images. And it offers dependable information to edge detection thin and track process.