SAR METHOD FOR DETECTING OIL SPILLS ON SATELLITE SAR IMAGES USING ARTIFICIAL NEURAL NETWORK

摘要

The present invention relates to an oil leakage detection method using a satellite SAR-based artificial neural network that detects an oil leak per pixel by applying an artificial neural network (ANN) method based on a SAR image, which is a high-resolution all-weather active microwave sensor. Obtaining a SAR image by examining a spatial distribution of an oil distribution using a satellite SAR; And investigating the temporal dispersion of the oil distribution from the acquired SAR image, wherein the investigating the temporal dispersion of the oil distribution comprises: specifying a constant size of a SAR image window, and setting the size of the set window. Designating (NxN) and calculating an average value (m), a standard deviation (std) and an average contrast ratio (σ); Normalizing a designated window of the SAR image; Removing artifacts from the normalized SAR image by using backscatter coefficient attenuation; Determining each pixel in the SAR image as one of oil spill and non-oil according to the calculated information; And outputting an oil outflow distribution result corresponding to the oil outflow range, comprising: identifying pixels corresponding to ships and artifacts and removing incident angle effects successfully from high resolution all-weather wide-area satellite SAR images using the neural network method As a result, oil spills can be detected.