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Proceedings Paper

Visibility improvement of shadow regions using hyperspectral band integration
Author(s): Paheding Sidike; Yakov Diskin; Saibabu Arigela; Vijayan K. Asari
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Paper Abstract

We present a hyperspectral image enhancement technique that utilizes spectral angle information to improve the local contrast of shadow regions and increases spatial resolution of the output color image determined by the enhancement process. The proposed visibility improvement technique is presented in a two-stage approach. The first stage of the algorithm improves the contrast within the image, thus enhancing the textural details of the scene. To minimize the effects of illumination variations on the visibility of objects in the scene, the spectral angle mapper (SAM) is employed, which allows the local pixel information to be insensitive to changes in illumination. A color restoration process is used to provide an enhanced color image from computed spectral angle between the reference spectrum and unknown spectra. This step enables us to colorize the output image along with the enhanced shadow regions. In the second stage, the spatial resolution of the contrast enhanced image is increased by using single image super resolution technique on the enhanced image. The super resolution technique employs a nonlinear interpolation based on multi-level local Fourier phase features. The combination of the enhancement, color restoration, and super resolution approaches provide better visibility of objects in the shadow regions. The effectiveness of the proposed technique is verified using realworld hyperspectral data.

Paper Details

Date Published: 23 October 2014
PDF: 13 pages
Proc. SPIE 9244, Image and Signal Processing for Remote Sensing XX, 92440V (23 October 2014); doi: 10.1117/12.2067073
Show Author Affiliations
Paheding Sidike, Univ. of Dayton (United States)
Yakov Diskin, Univ. of Dayton (United States)
Saibabu Arigela, Univ. of Dayton (United States)
Vijayan K. Asari, Univ. of Dayton (United States)


Published in SPIE Proceedings Vol. 9244:
Image and Signal Processing for Remote Sensing XX
Lorenzo Bruzzone, Editor(s)

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