NDLI: An inproved binary encoding algorithm for classification of hyperspectral images

Content Provider	IEEE Xplore Digital Library
Author	Huan Xie Xiaohua Tong
Copyright Year	2012
Description	Author affiliation: Dept. of Surveying & Geo-Inf., Tongji Univ., Shanghai, China (Huan Xie; Xiaohua Tong)
Abstract	Binary encoding is a standard technique in classifying hyperspectral images. In this paper, an improved binary encoding (IBE) approach is proposed to integrate spectra, texture, shape and height (if it is possible) information of hyperspectral image data into a binary encoding algorithm for automatically deriving class cover information. First connected regions are extracted from the hyperspectral data by applying a segmentation algorithm. The mean spectrum per region is considered representative for the region. Predefined parameters were used to describing the texture and shape of the region. Together with the spectral information these parameters and the corresponding height values from the height source are converted into a binary code. This code is then matched to that of a training data set for classification.
Starting Page	1
Ending Page	4
File Size	288395
Page Count	4
File Format	PDF
e-ISBN	9781479934065
DOI	10.1109/WHISPERS.2012.6874331
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-06-04
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Binary encoding Shape Urban areas Support vector machine classification Abstracts Classification Surface texture Hyperspectral image Hyperspectral imaging
Content Type	Text
Resource Type	Article

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