Improving the accuracy of detecting the edges of texture objects in remote sensing images

Abstract

The authors offer a method for detecting the edges of texture objects in remote sensing images. This method is based on the evaluation of textural and brightness attributes. It is proposed to use transition probabilities for three-dimensional Markov chains with two states as texture features, averaged within a sliding window. It makes possible to improve the detection accuracy of texture objects on multichannel or multi-time snapshots. To reduce the computational resources, it is proposed to determine the signs by the bit planes of the senior, most informative digits of the digital image. The simulation results confirm the effectiveness of the proposed method.