Abstract
This paper presents a novel framework for hyperspectral satellite image broadcasting over wireless channels. We present a new hyperspectral band ordering algorithm that improves the compression performance. The proposed scheme employs the 1D low-complexity Karhunen-Loève transform (KLT) that uses a clustering approach for spectral decorrelation. After that, the 2D DCT is applied to remove the redundant information from the spatial bands. The DCT components are quantized using a simple DC-quantization algorithm. After that, the transmission power is directly allocated to the quantized data according to their distributions and magnitudes without forward error correction (FEC). These data are transformed by Hadamard matrix and transmitted over a dense constellation. Experiments demonstrate that the proposed scheme improves the average image quality by 6.98dB and 3.48dB over LineCast and SoftCast, respectively, and it achieves up to 6.14dB gain over JPEG2000 with FEC.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Journal of Visual Communication and Image Representation
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
