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Marine oil spills affect the environment, economy, and quality of life for coastal inhabitants. This article presents a method of X-band marine radar oil-spill identification by considering the marine radar images of the 2010 Dalian 7-16 accident. The Prewitt operator was improved and a linear interpolation was proposed to suppress co-channel interferences. In addition, a model of a gray-intensity-correcting matrix is proposed to smooth a whole image, thus displaying the oil film more intuitively. Furthermore, a contrast-limited adaptive histogram equalization method was used to increase the contrast inside and outside the oil film. Moreover, the local adaptive thresholding method was improved to segment the oil spills. The results show that the proposed method is an improvement on similar previous approaches for this task when employing X-band marine radar images. The proposed method can provide technical and theoretical bases for emergency response, damage assessment, and liability identification of oil spills. [ABSTRACT FROM AUTHOR]

Oil spills cause damage in ocean environment. It is important to identify the oil spills for further treatment. We propose an oil spill detection method based on X-band marine radar image using texture analysis. In this method, first, received radar image was denoised by erasing co-channel interference and small speckles. Then, texture analysis was used to indicate the location of oil spills. In the texture analysis, we proposed a texture index calculated by four texture features of grey level co-occurrence matrix (GLCM). The texture index in oil spill area is higher than it in other place, which can be used for extracting oil spill area roughly. In the end, precise extraction of an oil spill was carried out by an adaptive thresholding algorithm on the area selected by the proposed texture index. According to the X-band marine radar images sampled in the oil spill accident on Xingang Port of Dalian, China, an oil spill detected by the proposed texture analysis method is comparable to visual interpretation. [ABSTRACT FROM AUTHOR]