RESEARCH ON DIFFERENTIAL CODING METHOD FOR SATELLITE REMOTE SENSING DATA COMPRESSION
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...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2012-07-01
|
| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XXXIX-B7/217/2012/isprsarchives-XXXIX-B7-217-2012.pdf |
| _version_ | 1831807239123369984 |
|---|---|
| author | Z. J. Lin N. Yao B. Deng C. Z. Wang J. H. Wang |
| author_facet | Z. J. Lin N. Yao B. Deng C. Z. Wang J. H. Wang |
| author_sort | Z. J. Lin |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-22T19:57:35Z |
| format | Article |
| id | doaj.art-876a2eece2754368b682e4a6290ea659 |
| institution | Directory Open Access Journal |
| issn | 1682-1750 2194-9034 |
| language | English |
| last_indexed | 2024-12-22T19:57:35Z |
| publishDate | 2012-07-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj.art-876a2eece2754368b682e4a6290ea6592022-12-21T18:14:23ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342012-07-01XXXIX-B721722210.5194/isprsarchives-XXXIX-B7-217-2012RESEARCH ON DIFFERENTIAL CODING METHOD FOR SATELLITE REMOTE SENSING DATA COMPRESSIONZ. J. Lin0N. Yao1B. Deng2C. Z. Wang3J. H. Wang4Chinese Academy of Surveying and Mapping, 16 Beitaiping Road, Beijing, ChinaRemote Sensing information Engineering School, Wuhan University, 129 Luoyu Road, Wuhan, ChinaBeijing Ceke Spatial Information Technology Company, Ltd., 16 Beitaiping Road, Beijing, ChinaGuizhou Guihang Unmanned Aerial Vehicles Company, Ltd., 87 West City Road, AnShun, ChinaGuizhou Guihang Unmanned Aerial Vehicles Company, Ltd., 87 West City Road, AnShun, ChinaData 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.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XXXIX-B7/217/2012/isprsarchives-XXXIX-B7-217-2012.pdf |
| spellingShingle | Z. J. Lin N. Yao B. Deng C. Z. Wang J. H. Wang RESEARCH ON DIFFERENTIAL CODING METHOD FOR SATELLITE REMOTE SENSING DATA COMPRESSION The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| title | RESEARCH ON DIFFERENTIAL CODING METHOD FOR SATELLITE REMOTE SENSING DATA COMPRESSION |
| title_full | RESEARCH ON DIFFERENTIAL CODING METHOD FOR SATELLITE REMOTE SENSING DATA COMPRESSION |
| title_fullStr | RESEARCH ON DIFFERENTIAL CODING METHOD FOR SATELLITE REMOTE SENSING DATA COMPRESSION |
| title_full_unstemmed | RESEARCH ON DIFFERENTIAL CODING METHOD FOR SATELLITE REMOTE SENSING DATA COMPRESSION |
| title_short | RESEARCH ON DIFFERENTIAL CODING METHOD FOR SATELLITE REMOTE SENSING DATA COMPRESSION |
| title_sort | research on differential coding method for satellite remote sensing data compression |
| url | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XXXIX-B7/217/2012/isprsarchives-XXXIX-B7-217-2012.pdf |
| work_keys_str_mv | AT zjlin researchondifferentialcodingmethodforsatelliteremotesensingdatacompression AT nyao researchondifferentialcodingmethodforsatelliteremotesensingdatacompression AT bdeng researchondifferentialcodingmethodforsatelliteremotesensingdatacompression AT czwang researchondifferentialcodingmethodforsatelliteremotesensingdatacompression AT jhwang researchondifferentialcodingmethodforsatelliteremotesensingdatacompression |