| Edge detection is an important part of remote sensing image processing for the detection of oil-spills on the sea. To detect the oil-spills more effectively, in this paper the author makes some improvements to the Pal. King fuzzy edge detection algorithm and presents a new algorithm that combines fuzzy enhancement theory and Genetic Algorithms (GA) to get the edge of oil-spills image according to the two main characteristics of the oil-spills image-one is the shape of oil-spills is unfixed and the other is the edge between the oil and water is fuzzy.The Pal. King algorithm has a good capacity for the detection of fuzzy edge and thin edge through improving the contrast between the two sides of edge, but with complex and big calculation on the one hand and the fixed threshold value doesn't fit for the different kind of images processing on the other hand. The algorithm presented here is composed of two parts: improved fuzzy enhancement algorithm that simplifies the complex G and G-1 calculation in the Pal. King algorithm, twice-optimization GA that can get the threshold value in the enhancement algorithm precisely and quickly to the different kind of image processing.At last, the author gives both its image edge processing result and other algorithms'. Through comparison, we can see that the oil's edge is more legible and continuous than the other algorithms' and oil-spills on the sea is easier and faster to be identified.
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