Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XXXIX-B7, 217-222, 2012
http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XXXIX-B7/217/2012/
doi:10.5194/isprsarchives-XXXIX-B7-217-2012
© Author(s) 2012. This work is distributed
under the Creative Commons Attribution 3.0 License.
 
31 Jul 2012
RESEARCH ON DIFFERENTIAL CODING METHOD FOR SATELLITE REMOTE SENSING DATA COMPRESSION
Z. J. Lin1, N. Yao2, B. Deng3, C. Z. Wang4, and J. H. Wang4 1Chinese Academy of Surveying and Mapping, 16 Beitaiping Road, Beijing, China
2Remote Sensing information Engineering School, Wuhan University, 129 Luoyu Road, Wuhan, China
3Beijing Ceke Spatial Information Technology Company, Ltd., 16 Beitaiping Road, Beijing, China
4Guizhou Guihang Unmanned Aerial Vehicles Company, Ltd., 87 West City Road, AnShun, China
Keywords: Satellite, Compression, Land cover, Differential encoding, Information amount, Compression rate Abstract. Data compression, in the process of Satellite Earth data transmission, is of great concern to improve the efficiency of data transmission. Information amounts inherent to remote sensing images provide a foundation for data compression in terms of information theory. In particular, distinct degrees of uncertainty inherent to distinct land covers result in the different information amounts. This paper first proposes a lossless differential encoding method to improve compression rates. Then a district forecast differential encoding method is proposed to further improve the compression rates. Considering the stereo measurements in modern photogrammetry are basically accomplished by means of automatic stereo image matching, an edge protection operator is finally utilized to appropriately filter out high frequency noises which could help magnify the signals and further improve the compression rates. The three steps were applied to a Landsat TM multispectral image and a set of SPOT-5 panchromatic images of four typical land cover types (i.e., urban areas, farm lands, mountain areas and water bodies). Results revealed that the average code lengths obtained by the differential encoding method, compared with Huffman encoding, were more close to the information amounts inherent to remote sensing images. And the compression rates were improved to some extent. Furthermore, the compression rates of the four land cover images obtained by the district forecast differential encoding method were nearly doubled. As for the images with the edge features preserved, the compression rates are average four times as large as those of the original images.
Conference paper (PDF, 850 KB)


Citation: Lin, Z. J., Yao, N., Deng, B., Wang, C. Z., and Wang, J. H.: RESEARCH ON DIFFERENTIAL CODING METHOD FOR SATELLITE REMOTE SENSING DATA COMPRESSION, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XXXIX-B7, 217-222, doi:10.5194/isprsarchives-XXXIX-B7-217-2012, 2012.

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