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A Hierarchical Approach to Landform Classification of Satellite Images Using a Fusion Strategy

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Computer Vision, Graphics and Image Processing

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4338))

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Abstract

There is increasing need for effective delineation of meaningfully different landforms due to the decreasing availability of experienced landform interpreters. Any procedure for automating the process of landform segmentation from satellite images offer the promise of improved consistency and reliality. We propose a hierarchical method for landform classification for classifying a wide variety of landforms. At stage 1 an image is classified as one of the three broad categories of terrain types in terms of its geomorphology, and these are: desertic/rann of kutch, coastal or fluvial. At stage 2, all different landforms within either desertic/rann of kutch , coastal or fluvial areas are identified using suitable processing. At the final stage, all outputs are fused together to obtain a final segmented output. The proposed technique is evaluated on large number of optical band satellite images that belong to aforementioned terrain types.

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© 2006 Springer-Verlag Berlin Heidelberg

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Gagrani, A., Gupta, L., Ravindran, B., Das, S., Roychowdhury, P., Panchal, V.K. (2006). A Hierarchical Approach to Landform Classification of Satellite Images Using a Fusion Strategy. In: Kalra, P.K., Peleg, S. (eds) Computer Vision, Graphics and Image Processing. Lecture Notes in Computer Science, vol 4338. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11949619_13

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  • DOI: https://doi.org/10.1007/11949619_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-68301-8

  • Online ISBN: 978-3-540-68302-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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