Improved JPEG performance in conjunction with cloud editing for Remote Sensing applications.

Hou, P. and Petrou, M. and Underwood, C. and Hojjatoleslami, A. (2000) Improved JPEG performance in conjunction with cloud editing for Remote Sensing applications. Geoscience and Remote Sensing, IEEE Transactions on, 38 (1). 515 -524. ISSN 0196-2892. (The full text of this publication is not available from this repository)

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Abstract

The authors propose an improved version of JPEG coding for compressing remote sensing images obtained by optical sensors onboard microsatellites. The approach involves expanding cloud features to include their cloud-land transitions, thereby simplifying their coding and subsequent compression. The system is fully automatic and appropriate for onboard implementation. Its improvement in coding stems from the realization that a large number of bits are used for coding the blocks that contain the transition regions between bright clouds, if present in the image, and the dark background. A fully automatic cloud-segmentation algorithm is therefore used to identify the external boundaries of the clouds, then smooth the corresponding blocks prior to coding. Further gains are also achieved by modifying the quantization table used for coding the coefficients of the discrete cosine transform. Compared to standard JPEG, at the same level of reconstruction quality, the new method can achieve compression ratio improvement by 13-161%, depending upon the context and the amount of cloud present in the specific image. The results are demonstrated with the help of several real images obtained by the University of Surrey, U.K., satellites

Item Type: Article
Subjects: Q Science > QC Physics > QC807 Geophysics (for Applied Geophysics see TN269)
Q Science
Q Science > QA Mathematics (inc Computing science) > QA801 Analytic mechanics
Divisions: Faculties > Science Technology and Medical Studies > School of Mathematics Statistics and Actuarial Science > Applied Mathematics
Faculties > Science Technology and Medical Studies > School of Engineering and Digital Arts > Image and Information Engineering
Faculties > Science Technology and Medical Studies > School of Computing > Security Group
Depositing User: Sayed Ali Hojjatoleslami
Date Deposited: 19 May 2011 10:47
Last Modified: 19 May 2011 10:47
Resource URI: http://kar.kent.ac.uk/id/eprint/27605 (The current URI for this page, for reference purposes)
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