A new algorithm for water information extraction from high resolution remote sensing imagery

Current algorithms that utilize water index to extract water information from high resolution remote sensing image are inadequate in that it is difficult to determine the optimal thresholds, the result of water boundary is not satisfactory and prone to error. We propose a new algorithm which combines image segmentation algorithm based on MRF model with Normalized Difference Water Index (NDWI) for extracting water information. We represent the pixels in image as random variables in a MRF model and introduce a hybrid feature space in the energy function on these variables, then minimize the energy function by iterative graph cut scheme to find the optimal water boundary. Water boundary is refined according to water index and color features of extracted main water body. The experiments on ShiLianghe Reservoir show that our approach can achieve a better accuracy and the boundary is precise, especially at the reservoirs that surrounding environments are complicated.