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Proceedings Paper

Spatio-spectral bilateral filters for hyperspectral imaging
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Paper Abstract

Due to the complex nature of hyper-spectra imaging, there are diversified noises in different bands of hyper-spectra image. Without proper pre-processing, these noises will lead to false target detection results in application. Furthermore, because of low signal to noise ratio, some bands, such as bands affected by water vapor in the infrared wavelengths, cannot be utilized in the target detection task. To improve the performance of hyper-spectra applications, many noise removal technologies have been developed. Most traditional denoising approaches either take only single band image into account at a time or only consider spectra shape at one location a time. But these approaches could not deal effectively with the common noises in hyper-spectra image that change from band to band and from one spatial spot to another. Also most generalized smooth filters without local adaptation will lead to losses in spatial details at band images. We propose a denoising approach that is based on bilateral filtering, which takes both spectra and spatial information into account. By locally adapt to adjacent spectra distribution, this approach will have the advantage of effective noise removal while keeping the spatial details in the band images. We also proposed parameter estimation method for hyperspectral image bilateral filtering. The experiment results show that this approach deliver better performance under various noises than other approach, the low signal to noise ratio in some band images have been significantly improved.

Paper Details

Date Published: 11 April 2008
PDF: 7 pages
Proc. SPIE 6966, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIV, 69660O (11 April 2008); doi: 10.1117/12.786424
Show Author Affiliations
Honghong Peng, Rochester Institute of Technology (United States)
Raghuveer Rao, Rochester Institute of Technology (United States)
David W. Messinger, Rochester Institute of Technology (United States)

Published in SPIE Proceedings Vol. 6966:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIV
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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