Abstract
Remote sensing image segmentation algorithms are proposed for different thresholds with rough sets theory and fuzzy sets theory in this paper. The target and background fuzzy sets are gotten with the gray image as a fuzzy sets ; The target and background fuzzy sets are approximated by two rough fuzzy sets, the optimal image segmentation threshold is chosen by the optimal standard, Experimental results show that the proposed algorithms are more effective and flexible.
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Sun, Hj., Deng, Tq., Jiao, Yy. (2013). Remote Sensing Image Segmentation Based on Rough Entropy. In: Tan, Y., Shi, Y., Mo, H. (eds) Advances in Swarm Intelligence. ICSI 2013. Lecture Notes in Computer Science, vol 7929. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38715-9_49
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DOI: https://doi.org/10.1007/978-3-642-38715-9_49
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-38714-2
Online ISBN: 978-3-642-38715-9
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