Kaan Ersahin

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—A new approach for segmentation and classification of Polarimetric Synthetic Aperture Radar (POLSAR) data is proposed based on spectral graph partitioning. Since automated analysis techniques are often challenged due to the noisy properties of POLSAR data, human experts are employed to aid in the interpretation of such data in an operational setting.(More)
— Most of the recent research on polarimetric SAR classification focused on pixel-based techniques using the co-variance matrix representation. Since multiple channels are inherently provided in polarimetric data, conventional techniques for increasing the dimensionality of the observation, such as texture feature extraction, were ignored. In this paper, we(More)
— A new approach for classification of Polarimetric Synthetic Aperture Radar (POLSAR) data is proposed using segmentation that is formulated as a graph partitioning problem. This work is motivated by the fact that human experts are very good at visual interpretation and segmentation of POLSAR data, which is often challenging for automated analysis(More)
—A new method for segmenting polarimetric Synthetic Aperture Radar (POLSAR) data is proposed. Image segmentation is formulated as a graph partitioning problem. Spectral graph partitioning – known to provide perceptually plausible image segmentation results using one or more cues (e.g., similarity, proximity, contour continuity) – is applied on POLSAR image(More)
Chilko Lake sockeye constitute one of the largest salmon stocks in the Pacific Northwest, for which Fisheries and Oceans Canada has maintained a 55-year record, including partitioned freshwater and marine survival. The lake was also the site of fertilization experiments in the 1970s-1990s. This paper examined the use of spaceborne data from MERIS and(More)
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