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  • Salient object detection in hyperspectral imagery

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    91488_1.pdf (950.4Kb)
    Author(s)
    Liang, Jie
    Zhou, Jun
    Bai, Xiao
    Qian, Yuntao
    Griffith University Author(s)
    Zhou, Jun
    Year published
    2013
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    Abstract
    Object detection in hyperspectral images is an important task for many applications. While most traditional methods are pixel-based, many recent efforts have been put on extracting spatial-spectral features. In this paper, we introduce Itti's visual saliency model into the spectral domain for object detection. This enables the extraction of salient spectral features, which is related to the material property and spatial layout of objects, in the scale space. To our knowledge, this is the first attempt to combine hyperspectral data with salient object detection. Three methods have been implemented and compared to show how ...
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    Object detection in hyperspectral images is an important task for many applications. While most traditional methods are pixel-based, many recent efforts have been put on extracting spatial-spectral features. In this paper, we introduce Itti's visual saliency model into the spectral domain for object detection. This enables the extraction of salient spectral features, which is related to the material property and spatial layout of objects, in the scale space. To our knowledge, this is the first attempt to combine hyperspectral data with salient object detection. Three methods have been implemented and compared to show how color component in the traditional saliency model can be replaced by spectral information. We have performed experiments on selected images from three online hyperspectral datasets, and show the effectiveness of the proposed methods.
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    Conference Title
    2013 20TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP 2013)
    DOI
    https://doi.org/10.1109/ICIP.2013.6738493
    Copyright Statement
    © 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
    Subject
    Computer vision
    Publication URI
    http://hdl.handle.net/10072/57175
    Collection
    • Conference outputs

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