Satellite image compression by concurrent representations of wavelet blocks
Abstract This paper proposes a complete compression and coding scheme for on-board satellite applications considering the main on-board constraints: low computational power and easy bit rate control. The proposed coding scheme improves the performance of the current Consultative Committee for Space...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Delaunay, Xavier [verfasserIn] Chabert, Marie [verfasserIn] Charvillat, Vincent [verfasserIn] Morin, Géraldine [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2011 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Annals of telecommunications - Paris : Lavoisier, 1946, 67(2011), 1-2 vom: 21. Apr., Seite 71-80 |
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| Übergeordnetes Werk: |
volume:67 ; year:2011 ; number:1-2 ; day:21 ; month:04 ; pages:71-80 |
| Links: |
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| DOI / URN: |
10.1007/s12243-011-0252-0 |
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| Katalog-ID: |
SPR024753300 |
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| 245 | 1 | 0 | |a Satellite image compression by concurrent representations of wavelet blocks |
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| 520 | |a Abstract This paper proposes a complete compression and coding scheme for on-board satellite applications considering the main on-board constraints: low computational power and easy bit rate control. The proposed coding scheme improves the performance of the current Consultative Committee for Space Data Systems (CCSDS) recommendation for a low additional complexity. We consider post-transforms in the wavelet domain, select the best representation for each block of wavelet coefficients, and encode it into an embedded bit stream. After applying a classical wavelet transform of the image, several concurrent representations of blocks of wavelet coefficients are generated. The best representations are then selected according to a rate-distortion criterion. Finally, a specific bit-plane encoder derived from the CCSDS recommendation produces an embedded bit stream ensuring the easy rate control required. In this article, both the post-transforms and the best representation selection have been adapted to the low complexity constraint, and the CCSDS coder has been modified to compress post-transformed representations. | ||
| 650 | 4 | |a Image coding |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Satellite applications |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Transform coding |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Wavelet transforms |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Hadamard transforms |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Chabert, Marie |e verfasserin |4 aut | |
| 700 | 1 | |a Charvillat, Vincent |e verfasserin |4 aut | |
| 700 | 1 | |a Morin, Géraldine |e verfasserin |4 aut | |
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10.1007/s12243-011-0252-0 doi (DE-627)SPR024753300 (SPR)s12243-011-0252-0-e DE-627 ger DE-627 rakwb eng 620 ASE Delaunay, Xavier verfasserin aut Satellite image compression by concurrent representations of wavelet blocks 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This paper proposes a complete compression and coding scheme for on-board satellite applications considering the main on-board constraints: low computational power and easy bit rate control. The proposed coding scheme improves the performance of the current Consultative Committee for Space Data Systems (CCSDS) recommendation for a low additional complexity. We consider post-transforms in the wavelet domain, select the best representation for each block of wavelet coefficients, and encode it into an embedded bit stream. After applying a classical wavelet transform of the image, several concurrent representations of blocks of wavelet coefficients are generated. The best representations are then selected according to a rate-distortion criterion. Finally, a specific bit-plane encoder derived from the CCSDS recommendation produces an embedded bit stream ensuring the easy rate control required. In this article, both the post-transforms and the best representation selection have been adapted to the low complexity constraint, and the CCSDS coder has been modified to compress post-transformed representations. Image coding (dpeaa)DE-He213 Satellite applications (dpeaa)DE-He213 Transform coding (dpeaa)DE-He213 Wavelet transforms (dpeaa)DE-He213 Hadamard transforms (dpeaa)DE-He213 Chabert, Marie verfasserin aut Charvillat, Vincent verfasserin aut Morin, Géraldine verfasserin aut Enthalten in Annals of telecommunications Paris : Lavoisier, 1946 67(2011), 1-2 vom: 21. Apr., Seite 71-80 (DE-627)547663234 (DE-600)2391943-7 1958-9395 nnns volume:67 year:2011 number:1-2 day:21 month:04 pages:71-80 https://dx.doi.org/10.1007/s12243-011-0252-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 67 2011 1-2 21 04 71-80 |
| spelling |
10.1007/s12243-011-0252-0 doi (DE-627)SPR024753300 (SPR)s12243-011-0252-0-e DE-627 ger DE-627 rakwb eng 620 ASE Delaunay, Xavier verfasserin aut Satellite image compression by concurrent representations of wavelet blocks 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This paper proposes a complete compression and coding scheme for on-board satellite applications considering the main on-board constraints: low computational power and easy bit rate control. The proposed coding scheme improves the performance of the current Consultative Committee for Space Data Systems (CCSDS) recommendation for a low additional complexity. We consider post-transforms in the wavelet domain, select the best representation for each block of wavelet coefficients, and encode it into an embedded bit stream. After applying a classical wavelet transform of the image, several concurrent representations of blocks of wavelet coefficients are generated. The best representations are then selected according to a rate-distortion criterion. Finally, a specific bit-plane encoder derived from the CCSDS recommendation produces an embedded bit stream ensuring the easy rate control required. In this article, both the post-transforms and the best representation selection have been adapted to the low complexity constraint, and the CCSDS coder has been modified to compress post-transformed representations. Image coding (dpeaa)DE-He213 Satellite applications (dpeaa)DE-He213 Transform coding (dpeaa)DE-He213 Wavelet transforms (dpeaa)DE-He213 Hadamard transforms (dpeaa)DE-He213 Chabert, Marie verfasserin aut Charvillat, Vincent verfasserin aut Morin, Géraldine verfasserin aut Enthalten in Annals of telecommunications Paris : Lavoisier, 1946 67(2011), 1-2 vom: 21. Apr., Seite 71-80 (DE-627)547663234 (DE-600)2391943-7 1958-9395 nnns volume:67 year:2011 number:1-2 day:21 month:04 pages:71-80 https://dx.doi.org/10.1007/s12243-011-0252-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 67 2011 1-2 21 04 71-80 |
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10.1007/s12243-011-0252-0 doi (DE-627)SPR024753300 (SPR)s12243-011-0252-0-e DE-627 ger DE-627 rakwb eng 620 ASE Delaunay, Xavier verfasserin aut Satellite image compression by concurrent representations of wavelet blocks 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This paper proposes a complete compression and coding scheme for on-board satellite applications considering the main on-board constraints: low computational power and easy bit rate control. The proposed coding scheme improves the performance of the current Consultative Committee for Space Data Systems (CCSDS) recommendation for a low additional complexity. We consider post-transforms in the wavelet domain, select the best representation for each block of wavelet coefficients, and encode it into an embedded bit stream. After applying a classical wavelet transform of the image, several concurrent representations of blocks of wavelet coefficients are generated. The best representations are then selected according to a rate-distortion criterion. Finally, a specific bit-plane encoder derived from the CCSDS recommendation produces an embedded bit stream ensuring the easy rate control required. In this article, both the post-transforms and the best representation selection have been adapted to the low complexity constraint, and the CCSDS coder has been modified to compress post-transformed representations. Image coding (dpeaa)DE-He213 Satellite applications (dpeaa)DE-He213 Transform coding (dpeaa)DE-He213 Wavelet transforms (dpeaa)DE-He213 Hadamard transforms (dpeaa)DE-He213 Chabert, Marie verfasserin aut Charvillat, Vincent verfasserin aut Morin, Géraldine verfasserin aut Enthalten in Annals of telecommunications Paris : Lavoisier, 1946 67(2011), 1-2 vom: 21. Apr., Seite 71-80 (DE-627)547663234 (DE-600)2391943-7 1958-9395 nnns volume:67 year:2011 number:1-2 day:21 month:04 pages:71-80 https://dx.doi.org/10.1007/s12243-011-0252-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 67 2011 1-2 21 04 71-80 |
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10.1007/s12243-011-0252-0 doi (DE-627)SPR024753300 (SPR)s12243-011-0252-0-e DE-627 ger DE-627 rakwb eng 620 ASE Delaunay, Xavier verfasserin aut Satellite image compression by concurrent representations of wavelet blocks 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This paper proposes a complete compression and coding scheme for on-board satellite applications considering the main on-board constraints: low computational power and easy bit rate control. The proposed coding scheme improves the performance of the current Consultative Committee for Space Data Systems (CCSDS) recommendation for a low additional complexity. We consider post-transforms in the wavelet domain, select the best representation for each block of wavelet coefficients, and encode it into an embedded bit stream. After applying a classical wavelet transform of the image, several concurrent representations of blocks of wavelet coefficients are generated. The best representations are then selected according to a rate-distortion criterion. Finally, a specific bit-plane encoder derived from the CCSDS recommendation produces an embedded bit stream ensuring the easy rate control required. In this article, both the post-transforms and the best representation selection have been adapted to the low complexity constraint, and the CCSDS coder has been modified to compress post-transformed representations. Image coding (dpeaa)DE-He213 Satellite applications (dpeaa)DE-He213 Transform coding (dpeaa)DE-He213 Wavelet transforms (dpeaa)DE-He213 Hadamard transforms (dpeaa)DE-He213 Chabert, Marie verfasserin aut Charvillat, Vincent verfasserin aut Morin, Géraldine verfasserin aut Enthalten in Annals of telecommunications Paris : Lavoisier, 1946 67(2011), 1-2 vom: 21. Apr., Seite 71-80 (DE-627)547663234 (DE-600)2391943-7 1958-9395 nnns volume:67 year:2011 number:1-2 day:21 month:04 pages:71-80 https://dx.doi.org/10.1007/s12243-011-0252-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 67 2011 1-2 21 04 71-80 |
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10.1007/s12243-011-0252-0 doi (DE-627)SPR024753300 (SPR)s12243-011-0252-0-e DE-627 ger DE-627 rakwb eng 620 ASE Delaunay, Xavier verfasserin aut Satellite image compression by concurrent representations of wavelet blocks 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This paper proposes a complete compression and coding scheme for on-board satellite applications considering the main on-board constraints: low computational power and easy bit rate control. The proposed coding scheme improves the performance of the current Consultative Committee for Space Data Systems (CCSDS) recommendation for a low additional complexity. We consider post-transforms in the wavelet domain, select the best representation for each block of wavelet coefficients, and encode it into an embedded bit stream. After applying a classical wavelet transform of the image, several concurrent representations of blocks of wavelet coefficients are generated. The best representations are then selected according to a rate-distortion criterion. Finally, a specific bit-plane encoder derived from the CCSDS recommendation produces an embedded bit stream ensuring the easy rate control required. In this article, both the post-transforms and the best representation selection have been adapted to the low complexity constraint, and the CCSDS coder has been modified to compress post-transformed representations. Image coding (dpeaa)DE-He213 Satellite applications (dpeaa)DE-He213 Transform coding (dpeaa)DE-He213 Wavelet transforms (dpeaa)DE-He213 Hadamard transforms (dpeaa)DE-He213 Chabert, Marie verfasserin aut Charvillat, Vincent verfasserin aut Morin, Géraldine verfasserin aut Enthalten in Annals of telecommunications Paris : Lavoisier, 1946 67(2011), 1-2 vom: 21. Apr., Seite 71-80 (DE-627)547663234 (DE-600)2391943-7 1958-9395 nnns volume:67 year:2011 number:1-2 day:21 month:04 pages:71-80 https://dx.doi.org/10.1007/s12243-011-0252-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 67 2011 1-2 21 04 71-80 |
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Delaunay, Xavier @@aut@@ Chabert, Marie @@aut@@ Charvillat, Vincent @@aut@@ Morin, Géraldine @@aut@@ |
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Delaunay, Xavier |
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Delaunay, Xavier ddc 620 misc Image coding misc Satellite applications misc Transform coding misc Wavelet transforms misc Hadamard transforms Satellite image compression by concurrent representations of wavelet blocks |
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620 ASE Satellite image compression by concurrent representations of wavelet blocks Image coding (dpeaa)DE-He213 Satellite applications (dpeaa)DE-He213 Transform coding (dpeaa)DE-He213 Wavelet transforms (dpeaa)DE-He213 Hadamard transforms (dpeaa)DE-He213 |
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Satellite image compression by concurrent representations of wavelet blocks |
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Satellite image compression by concurrent representations of wavelet blocks |
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satellite image compression by concurrent representations of wavelet blocks |
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Satellite image compression by concurrent representations of wavelet blocks |
| abstract |
Abstract This paper proposes a complete compression and coding scheme for on-board satellite applications considering the main on-board constraints: low computational power and easy bit rate control. The proposed coding scheme improves the performance of the current Consultative Committee for Space Data Systems (CCSDS) recommendation for a low additional complexity. We consider post-transforms in the wavelet domain, select the best representation for each block of wavelet coefficients, and encode it into an embedded bit stream. After applying a classical wavelet transform of the image, several concurrent representations of blocks of wavelet coefficients are generated. The best representations are then selected according to a rate-distortion criterion. Finally, a specific bit-plane encoder derived from the CCSDS recommendation produces an embedded bit stream ensuring the easy rate control required. In this article, both the post-transforms and the best representation selection have been adapted to the low complexity constraint, and the CCSDS coder has been modified to compress post-transformed representations. |
| abstractGer |
Abstract This paper proposes a complete compression and coding scheme for on-board satellite applications considering the main on-board constraints: low computational power and easy bit rate control. The proposed coding scheme improves the performance of the current Consultative Committee for Space Data Systems (CCSDS) recommendation for a low additional complexity. We consider post-transforms in the wavelet domain, select the best representation for each block of wavelet coefficients, and encode it into an embedded bit stream. After applying a classical wavelet transform of the image, several concurrent representations of blocks of wavelet coefficients are generated. The best representations are then selected according to a rate-distortion criterion. Finally, a specific bit-plane encoder derived from the CCSDS recommendation produces an embedded bit stream ensuring the easy rate control required. In this article, both the post-transforms and the best representation selection have been adapted to the low complexity constraint, and the CCSDS coder has been modified to compress post-transformed representations. |
| abstract_unstemmed |
Abstract This paper proposes a complete compression and coding scheme for on-board satellite applications considering the main on-board constraints: low computational power and easy bit rate control. The proposed coding scheme improves the performance of the current Consultative Committee for Space Data Systems (CCSDS) recommendation for a low additional complexity. We consider post-transforms in the wavelet domain, select the best representation for each block of wavelet coefficients, and encode it into an embedded bit stream. After applying a classical wavelet transform of the image, several concurrent representations of blocks of wavelet coefficients are generated. The best representations are then selected according to a rate-distortion criterion. Finally, a specific bit-plane encoder derived from the CCSDS recommendation produces an embedded bit stream ensuring the easy rate control required. In this article, both the post-transforms and the best representation selection have been adapted to the low complexity constraint, and the CCSDS coder has been modified to compress post-transformed representations. |
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Satellite image compression by concurrent representations of wavelet blocks |
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https://dx.doi.org/10.1007/s12243-011-0252-0 |
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Chabert, Marie Charvillat, Vincent Morin, Géraldine |
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| doi_str |
10.1007/s12243-011-0252-0 |
| up_date |
2024-07-04T02:15:49.751Z |
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