Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Distributed Source Coding Techniques for Lossless Compression of Hyperspectral Images | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2007 Article ID 45493 13 pages doi 2007 45493 Research Article Distributed Source Coding Techniques for Lossless Compression of Hyperspectral Images Enrico Magli 1 Mauro Barni 2 Andrea Abrardo 2 and Marco Grangetto1 1 Center for Multimedia Radio Communications CERCOM Department of Electronics Politecnico di Torino 24 Corso Duca degli Abruzzi 10129 Torino Italy 2 Dipartimento di Ingegneria dell Informazione Universita di Siena Via Roma 56 59100 Siena Italy Received 10 February 2006 Revised 18 October 2006 Accepted 23 October 2006 Recommended by Yap-Peng Tan This paper deals with the application of distributed source coding DSC theory to remote sensing image compression. Although DSC exhibits a significant potential in many application fields up till now the results obtained on real signals fall short of the theoretical bounds and often impose additional system-level constraints. The objective of this paper is to assess the potential of DSC for lossless image compression carried out onboard a remote platform. We first provide a brief overview of DSC of correlated information sources. We then focus on onboard lossless image compression and apply DSC techniques in order to reduce the complexity of the onboard encoder at the expense of the decoder s by exploiting the correlation of different bands of a hyper-spectral dataset. Specifically we propose two different compression schemes one based on powerful binary error-correcting codes employed as source codes and one based on simpler multilevel coset codes. The performance of both schemes is evaluated on a few AVIRIS scenes and is compared with other state-of-the-art 2D and 3D coders. Both schemes turn out to achieve competitive compression performance and one of them also has reduced complexity. Based on these results we highlight the main issues that are still to be solved to further improve the performance of DSC-based .
