Abstract— An effective and precise method for shoreline detection from satellite imagery is presented. The algorithm is based on two main steps: (1) the detection of singularities in a single image using non-separable wavelet and (2)amendment procedure using distance regularized level set evolution scheme. Firstly, by selecting appropriate parameters, the non-separable wavelet filter banks which can provide information of different orientations are used to capture the singularities of the selected single satellite image; Secondly, obtaining the modulus image by utilizing sub-images decomposed from the non-separable wavelet filter banks; Thirdly, extracting the shoreline iteratively with the use of distance regularized level set evolution scheme. Experiments are conducted and results show that the proposed algorithm is applicable to satellite imagery, and the shoreline is robust to noises as well as blurring.
Index Terms— Shoreline detection, non-separable wavelet, Satellite imagery, edge detection, level set method, distance regularized level set evolution.
Duanquan Xu is with Electronics and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, China (e-mail: email@example.com).
Cite: A New Algorithm for Shoreline Extraction from Satellite Imagery with Non-Separable Wavelet and Level Set Method, " Shujian Yu, Yi Mou, Duanquan Xu, Xinge You, Long Zhou, and Wu Zeng," International Journal of Machine Learning and Computing vol. 3, no. 1, pp. 158-163, 2013.