Material segmentation in hyperspectral images with minimal region perimeters

Yu Zhang, Cong Phuoc Huynh, Nariman Habili, King Ngi Ngan

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    5 Citations (Scopus)

    Abstract

    We propose a supervised approach to the classification and segmentation of material regions in hyperspectral imagery. Our algorithm is a two-stage process, combining a pixelwise classification step with a segmentation step aiming to minimise the total perimeters of the resulting regions. Our algorithm is distinctive in its ability to ensure label consistency within local homogeneous areas and to generate material segments with smooth boundaries. Furthermore, we establish a new hyperspectral benchmark dataset to demonstrate the advantages of the proposed approach over several state-of-the-art methods.

    Original languageEnglish
    Title of host publication2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings
    PublisherIEEE Computer Society
    Pages834-838
    Number of pages5
    ISBN (Electronic)9781467399616
    DOIs
    Publication statusPublished - 3 Aug 2016
    Event23rd IEEE International Conference on Image Processing, ICIP 2016 - Phoenix, United States
    Duration: 25 Sept 201628 Sept 2016

    Publication series

    NameProceedings - International Conference on Image Processing, ICIP
    Volume2016-August
    ISSN (Print)1522-4880

    Conference

    Conference23rd IEEE International Conference on Image Processing, ICIP 2016
    Country/TerritoryUnited States
    CityPhoenix
    Period25/09/1628/09/16

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