Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/10494
Title: Multispectral image compression by cluster-adaptive subspace representation
Authors: Shen, HL
Li, K
Xin, JH 
Keywords: Cellulose
Hydrophobicity
Nanopartilces
Roughness
Silica
Issue Date: 2010
Source: Proceedings - International Conference on Image Processing, ICIP, 2010, 5652058, p. 521-524 How to cite?
Abstract: Multispectral imaging has attracted much interest in color science area, for its ability in providing much more spectral information than 3-channel color images. Due to the huge data volume, it is necessary to compress multispectral images for efficient transmission. This paper proposes a framework for spectral compression of multispectral image by using clusteradaptive subspaces representation. In the framework, multispectral image is initially segmented by hierarchical analysis of the transform coefficients in the global subspace, and then ambiguous pixels are identified and classified into proper clusters based on linear discriminant analysis. The dimensionality of each adaptive subspace is determined by specified reconstruction error level, followed by further cluster splitting if necessary. The efficiency of the proposed method is verified by experiments on real multispectral images.
Description: 2010 17th IEEE International Conference on Image Processing, ICIP 2010, Hong Kong, 26-29 September 2010
URI: http://hdl.handle.net/10397/10494
ISBN: 9781424479948
ISSN: 1522-4880
DOI: 10.1109/ICIP.2010.5652058
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