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• W2022137318 abstract "Abstract. In this paper we investigate the performance of an algorithm for automatic segmentation of full polarimetric, synthetic aperture radar (SAR) sea ice scenes. The algorithm uses statistical and polarimetric properties of the backscattered radar signals to segment the SAR image into a specified number of classes. This number was determined in advance from visual inspection of the SAR image and by available in-situ measurements. The segmentation result was then compared to ice charts drawn by ice service analysts. The comparison revealed big discrepancies between the charts of the analysts, and between the manual and the automatic segmentations. In the succeeding analysis, the automatic segmentation chart was labeled into ice types by sea ice experts, and the SAR features used in the segmentation were interpreted in terms of physical sea ice properties. Studies of automatic and robust estimation of the number of ice classes in SAR sea ice scenes will be highly relevant for future work." @default.
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• W2022137318 date "2013-06-13" @default.
• W2022137318 modified "2023-09-26" @default.
• W2022137318 title "Comparison of automatic segmentation of full polarimetric SAR sea ice images with manually drawn ice charts" @default.
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• W2022137318 doi "https://doi.org/10.5194/tcd-7-2595-2013" @default.
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