Publication: Performance analysis of edge detection algorithms with THEOS satellite images
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2017
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en
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item.page.harrt.identifier.callno
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2017 International Conference on Digital Arts; Media and Technology (ICDAMT)
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235
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239
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Performance analysis of edge detection algorithms with THEOS satellite images
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Abstract
The goal of this research is to find a suitable edge detection algorithm with 4 bands; B1; B2; B3; and B4 of different types of satellite image. In this paper; the dataset is derived from raw satellite images; namely THEOS; of the seashore in the Samut Prakan province; a fruit garden in the Chantaburi province and river line in Ayuthaya provinces. Edge detection performance algorithms are Signal-to-Noise Ratio (PSNR); Mean Square Error (MSE); and edge detection processing time; as well as qualitative human visual perception. Our result shows that Canny algorithm and Laplacian of Gaussian algorithm were the best edge detection algorithm for both qualitatively and quantitatively. Moreover; the different kinds of bands in satellite images illustrated the same result. All of the algorithms consumed similar times.