In this paper, we propose a lossless compression method to resolve the limitations in the real-time transmission of aurora spectral images. This method bi-dimensionally decorrelates the spatial and spectral domains and effectively removes side information of recursively computed coefficients to achieve high quality rapid compression. Experiments on data sets captured from the Antarctic Zhongshan Station show that the proposed algorithm can meet real-time requirements by using parallel processing to achieve outstanding compression ratio performance with low computational complexity.

Lossless compression for aurora spectral images using fast online bi-dimensional decorrelation method / W. Kong, J. Wu, Z. Hu, M. Anisetti, E. Damiani, G. Jeon. - In: INFORMATION SCIENCES. - ISSN 0020-0255. - 381(2017), pp. 33-45. [10.1016/j.ins.2016.11.008]

Lossless compression for aurora spectral images using fast online bi-dimensional decorrelation method

M. Anisetti;E. Damiani
Penultimo
;
2017

Abstract

In this paper, we propose a lossless compression method to resolve the limitations in the real-time transmission of aurora spectral images. This method bi-dimensionally decorrelates the spatial and spectral domains and effectively removes side information of recursively computed coefficients to achieve high quality rapid compression. Experiments on data sets captured from the Antarctic Zhongshan Station show that the proposed algorithm can meet real-time requirements by using parallel processing to achieve outstanding compression ratio performance with low computational complexity.
Aurora spectral images; Bi-dimensional decorrelation; Lossless compression; Online; Parallel; Control and Systems Engineering; Theoretical Computer Science; Software; Computer Science Applications; Computer Vision and Pattern Recognition; Information Systems and Management; Artificial Intelligence
Settore INF/01 - Informatica
2017
Article (author)
File in questo prodotto:
File Dimensione Formato  
loseless.pdf

accesso riservato

Tipologia: Publisher's version/PDF
Dimensione 1.93 MB
Formato Adobe PDF
1.93 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/470640
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 9
  • ???jsp.display-item.citation.isi??? 9
social impact