Research on oil spill identification based on texture features-a case study of “Hebei Spirit” accident

For single-band and single-polarized SAR, its capability to monitor oil spill is limited based on image intensity. Texture features are suggested to improve accuracy of oil spill surveillance. Texture measures, extracted from GLCM (gray-level co-occurrence matrices), are analyzed, which indicates that mean, contrast, variance, entropy, and dissimilarity are effective for oil identification. SAR image is characterized by high resolution and speckle noise, which limits pixel-based approaches. In this paper, object oriented image analysis is used to extract oil slick. This algorithm typically incorporates both spectral and spatial information in the image segmentation phase. Results indicate that texture features extend features of interested objects, and help to improve oil spill surveillance.