SAR images thresholding for oil spill detection

This paper presents a new algorithm for Synthetic Aperture Radar (SAR) images segmentation based on thresholding technique for oil spill detection. Generally, segmentation of a SAR image falls into two categories; one based on grey levels and the other based on texture. The present paper deals with SAR images segmentation based on grey levels. We developed a new formula using between class variance method for estimating optimal threshold value based on Gamma distribution. We assume that the data in SAR image is modeled a Gamma distribution; that means histogram of SAR images is assumed a mixture of Gamma distributions. The proposed method is iterative which decreases the number of operation to converge tends to the optimal solution. It is applied on bi-modal and multimodal scenarios. The results obtained are promising.