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Proceedings Paper

Remote sensing image enhancement integrating its local statistical characteristics
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Paper Abstract

Remote sensing is widely used to assess the destruction from natural disasters and to plan relief and recovery operations. How to automatically extract useful features and segment interesting objects from digital images, including remote sensing imagery, becomes a critical task for image understanding. Unfortunately, the data collection of aerial digital images is constrained with bad weather, muzzy atmosphere, and unstable camera or camcorder. As a result, remote sensing imagery is shown as lowcontrast, blurred, and dark from time to time. Here, we introduce a new method integrating image local statistics and image natural characteristics to enhance remote sensing imagery. This method computes the adaptive histogram equalization to each distinct region of the input image and then redistributes the lightness values of the image. The natural characteristic of image is applied to adjust the restoration contrast. The experiments on real data show the effectiveness of the algorithm.

Paper Details

Date Published: 18 January 2010
PDF: 6 pages
Proc. SPIE 7529, Image Quality and System Performance VII, 75290O (18 January 2010); doi: 10.1117/12.838472
Show Author Affiliations
Qiang He, Mississippi Valley State Univ. (United States)
Chee-Hung Henry Chu, Univ. of Louisiana at Lafayette (United States)


Published in SPIE Proceedings Vol. 7529:
Image Quality and System Performance VII
Susan P. Farnand; Frans Gaykema, Editor(s)

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