arrow
Return

Hyperspectral image coding and transmission scheme based on wavelet transform and distributed source coding

delete2016-11-23
delete5
PRE
AI
A
Ahmed Hagag *
范
范晓鹏 (Xiaopeng Fan)
F
Fathi E. Abd El‐Samie
DOI:10.1007/s11042-016-4158-8delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
This paper presents a novel scheme for satellite hyperspectral images broadcasting over wireless channels. First, a simple pre-processing is performed. Then, a new hyperspectral band ordering algorithm that improves the compression performance is implemented. The ordered image data is also normalized. The discrete wavelet transform with three-level decomposition is used to divide each hyperspectral image band into ten wavelet sub-bands; nine of them are the details and the last LL-LL-LL is an approximation version of the band. Coset coding based on distributed source coding (DSC) is used for the LL-LL-LL sub-band to achieve high compression efficiency and low encoding complexity. Then, without syndrome coding, the transmission power is allocated directly to the band details and coset values according to their distributions and magnitudes without forward error correction (FEC). Finally, these data are transformed by the Hadamard matrix and transmitted over a dense constellation. Satellite hyperspectral images from an Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) satellite are used for the validation of the proposed scheme. Experimental results demonstrate that the proposed scheme improves the average image quality by 6.91, 3.00 and 7.68 dB over LineCast, SoftCast-3D, and Softcast-2D, respectively. It also achieves up to a 5.63 dB gain over JPEG2000 with FEC.
Keywords:
Joint source-channel code (JSCC)
Wireless communication
Hyperspectral band ordering
AVIRIS
Wavelet transforms
DSC
LineCast
SoftCast
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Multimedia Tools and Applications cover
Multimedia Tools and Applications
IF:
3
Papers:
2.0W
Citations:
3.2W

Organization

H
harbin institute of technology
Scholars:
8.0W
Papers: 6.6W
Citations: 66
M
menofia university
Scholars:
2.8K
Papers: 2.3K
Citations: 4
Cited Papers

Cited Papers

err2002-01-01
err0
PREAI
errPratibha L. Gai
errShare
errSave
Sampling from Gaussian Markov random fields conditioned on linear constraints
err2008-07-17
err0
PREAI
errDaniel Peter Simpson; Ian W. Turner; A. N. Pettitt
errShare
errSave
Transform coding techniques for lossy hyperspectral data compression
err2007-05-01
err249
PREAI
errPenna, Barbara; Tillo, Tammam; Magli, Enrico; Olmo, Gabriella
errShare
errSave
errShare
errSave
The Role of Multiple Large Shareholders in the Choice of Debt Source
err2016-11-04
err0
PREAI
errSabri Boubaker; Wael Rouatbi; Walid Saffar
errShare
errSave
Soluble urokinase plasminogen activator receptor (suPAR) is a novel, independent predictive marker of myocardial infarction in HIV‐1‐infected patients: a nested case‐control study
err2015-09-14
err0
errOAAI
errLJH Rasmussen; A Knudsen; TL Katzenstein; J Gerstoft; N Obel; NR Jørgensen; G Kronborg; T Benfield; A Kjær; J Eugen‐Olsen; A‐M Lebech
errShare
errSave
researcher View more