A PCA-FVQ and 3D-SPECK combined hierarchical coding method for spectral imagery

In this paper, a hierarchical spectral imagery coding method has been proposed. The spectral imagery is encoded into two layers, i.e. base layer and enhancement layer. Firstly, an PCA-FVQ (Principal Component Analysis based Fast Vector Quantization) coding method has been proposed to generate the ba...

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Published in:2012 IEEE 11th International Conference on Signal Processing Vol. 2; pp. 1038 - 1042
Main Authors: Yue, Yunfeng, Zhuo, Li, Wang, Suyu, Zhao, Yingdi, Shi, Chen
Format: Conference Proceeding
Language:English
Published: IEEE 01.10.2012
Subjects:
3D-SPECK
Binary sequences
Correlation
Encoding
Image coding
Image quality
Image reconstruction
Indexes
Principal component analysis
Signal to noise ratio
spectral imagery
Vector quantization
ISBN:9781467321969, 1467321966
ISSN:2164-5221
Online Access:Get full text
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Abstract In this paper, a hierarchical spectral imagery coding method has been proposed. The spectral imagery is encoded into two layers, i.e. base layer and enhancement layer. Firstly, an PCA-FVQ (Principal Component Analysis based Fast Vector Quantization) coding method has been proposed to generate the base layer bitstream, which can be decoded independently to provide a basic image quality. Then the differential data between the original image and the reconstructed image decoded from the base layer bitstream is encoded by 3D-SPECK algorithm to generate the enhancement layer bitstream which can provide an enhanced image quality. The experimental results show that, under the same coding conditions, compared with 3D-SPECK algorithm, the proposed method has achieved 1-15dB higher image quality improvement in terms of SNR (Signal to Noise) while the compression ratio can be controlled precisely.
AbstractList In this paper, a hierarchical spectral imagery coding method has been proposed. The spectral imagery is encoded into two layers, i.e. base layer and enhancement layer. Firstly, an PCA-FVQ (Principal Component Analysis based Fast Vector Quantization) coding method has been proposed to generate the base layer bitstream, which can be decoded independently to provide a basic image quality. Then the differential data between the original image and the reconstructed image decoded from the base layer bitstream is encoded by 3D-SPECK algorithm to generate the enhancement layer bitstream which can provide an enhanced image quality. The experimental results show that, under the same coding conditions, compared with 3D-SPECK algorithm, the proposed method has achieved 1-15dB higher image quality improvement in terms of SNR (Signal to Noise) while the compression ratio can be controlled precisely.
Author Zhuo, Li
Wang, Suyu
Zhao, Yingdi
Shi, Chen
Yue, Yunfeng
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  organization: Signal and Information Processing Laboratory, Beijing University of Technology, China
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  organization: Signal and Information Processing Laboratory, Beijing University of Technology, China
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  givenname: Chen
  surname: Shi
  fullname: Shi, Chen
  organization: Signal and Information Processing Laboratory, Beijing University of Technology, China
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Snippet In this paper, a hierarchical spectral imagery coding method has been proposed. The spectral imagery is encoded into two layers, i.e. base layer and...
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StartPage 1038
SubjectTerms 3D-SPECK
Binary sequences
Correlation
Encoding
Image coding
Image quality
Image reconstruction
Indexes
Principal component analysis
Signal to noise ratio
spectral imagery
Vector quantization
Title A PCA-FVQ and 3D-SPECK combined hierarchical coding method for spectral imagery
URI https://ieeexplore.ieee.org/document/6491756
Volume 2
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