NDLI: Edge-Based Prediction for Lossless Compression of Hyperspectral Images

Content Provider	IEEE Xplore Digital Library
Author	Jain, S.K. Adjeroh, D.A.
Copyright Year	2007
Description	Author affiliation: Lane Dept. of Comput. Sci., West Virginia Univ., Morgantown, WV (Jain, S.K.; Adjeroh, D.A.)
Abstract	We present two algorithms for error prediction in lossless compression of hyperspectral images. The algorithms are context-based and non-linear, and use a one-band look-ahead, thus requiring a minimal storage buffer. The first algorithm (NPHI) predicts the pixel in the current band based on the information from its context. Prediction contexts are defined based on the neighboring causal pixels in the current band and the corresponding co-located causal pixels in the reference band. EPHI extends NPHI using edge-based analysis. Prediction is performed by classifying the pixels into edge and non-edge pixels. Each pixel is then predicted using information from pixels in the same edge class within the context. Empirical results show that the proposed methods produce competitive results when compared with other state-of-the-art algorithms with comparable complexity. On average, the edge-based technique (EPHI) produced the best overall result, over the images in the test dataset
Starting Page	153
Ending Page	162
File Size	279819
Page Count	10
File Format	PDF
ISBN	0769527914
ISSN	10680314
DOI	10.1109/DCC.2007.36
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-03-27
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image coding Hyperspectral imaging Hyperspectral sensors Infrared spectra Electromagnetic wave absorption Prediction algorithms Image storage Layout Infrared image sensors Pixel
Content Type	Text
Resource Type	Article
Subject	Computer Networks and Communications

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