Spatial pattern alterations from JPEG2000 lossy compression of remote sensing images: Massive variogram analysis in high performance computing

Journal of Applied Remote Sensing

Volumn 7, Issue 1, 2013, Pages

  Pesquer, Lluís ^a   Pons, Xavier ^b   Cortés, Ana ^b   Serral, Ivette ^a  

^a CREAF   (Spain)

^b UNIVERSITAT AUTÒNOMA DE BARCELONA   (Spain)

Author keywords

Geostatistics; High performance computing; Lossy compression; Remote sensing images

Indexed keywords

IMAGE ANALYSIS; RADIOMETERS; REMOTE SENSING; TIME DOMAIN ANALYSIS;

COMPACT AIRBORNE SPECTROGRAPHIC IMAGER; DISTRIBUTED ENVIRONMENTS; GEO-STATISTICS; HIGH PERFORMANCE COMPUTING; LOSSY COMPRESSIONS; MODERATE RESOLUTION IMAGING SPECTRORADIOMETER; REMOTE SENSING IMAGES; THREE-DIMENSIONAL COMPRESSION;

IMAGE COMPRESSION;

EID: 84883188846     PISSN: None     EISSN: 19313195     Source Type: Journal    
DOI: 10.1117/1.JRS.7.073595     Document Type: Article

References (53)

1. J. R. Jensen, Introductory Digital Image Processing: A Remote Sensing Perspective, 3rd ed., Prentice Hall Series in Geographic Information Science (2005).
2. P. Serra and X. Pons, "Monitoring farmers decisions on Mediterranean irrigated crops using satellite image time series," Int. J. Rem. Sens. 29(8), 2293-2316 (2008), http://dx.doi.org/10.1080/01431160701408444.
3. P. Schneider and S. J. Hook, "Space observations of inland water bodies show rapid surface warming since 1985," Geophys. Res. Lett. 37(22), L22405 (2010), http://dx.doi.org/10.1029/2010GL045059.
4. N. B. Chang et al., "Change detection of land use and land cover in an urban region with SPOT-5 images and partial Lanczos extreme learning machine," J. Appl. Remote Sensing 4(1), 043551 (2010), http://dx.doi.org/ 10.1117/1.3518096.
5. K. Richter et al., "Plant growth monitoring and potential drought risk assessment by means of Earth observation data," Int. J. Rem. Sens. 29(17), 4943-4960 (2008), http://dx.doi.org/10.1080/01431160802036268.
6. T. M. Lillesand, R. W. Kiefer, and J. W. Chipman, Remote Sensing and Image Interpretation, 5th ed., John Wiley and Sons, New York (2004).
7. D. S. Taubman and M. W. Marcellin, JPEG 2000: Image Compression Fundamentals, Standards, and Practice, pp. 778, Kluwer Academic Publishers, Dordrecht (2002).
8. T. Ranchin and L. Wald, "The wavelet transform for the analysis of remotely sensed images," Int. J. Rem. Sens. 14(3), 615-619 (1993), http://dx.doi.org/10.1080/01431169308904362.
9. G. Martín et al., "Impact of JPEG2000 compression on endmember extraction and unmixing of remotely sensed hyperspectral data," J. Appl. Rem. Sens. 4(1) 041796 (2010), http://dx.doi.org/10.1117/1.3474975.
10. A. Zabala and X. Pons, "Effects of lossy compression on remote sensing image classification of forest areas," Int. J. Appl. Earth Observat. Geoinf. 13(1), 43-51 (2011), http://dx.doi.org/10.1016/j.jag.2010.06. 005.
11. M. A. Chaudhry et al., "Optimization of wavelet bases for texture analysis," in Proc. Fifth IEEE International Symposium on Signal Processing and Information Technology, Athens, pp. 789-793 (2005).
12. Y. Li et al., "Adaptive compression of remote sensing stereo image pairs," J. Appl. Rem. Sens. 4(1), 041777 (2010), http://dx.doi.org/10.1117/ 1.3495716.
13. A. Zabala et al., "Implications of JPEG2000 lossy compression on multiple regression modeling," Proc. SPIE 6749, 674918 (2007), http://dx.doi.org/10.1117/12.738028.
14. M. Kiefner and M. Hahn, "Image compression versus matching accuracy," in International Archives of Photogrammetry and Remote Sensing, Vol. XXXIII, Part B2, pp. 316-323 (2000).
15. P. J. Curran and P. M. Atkinson, "Geostatistics and remote sensing," Prog. Phys. Geogr. 22(1), 61-78 (1998), http://dx.doi.org/10. 1177/030913339802200103.
16. C. S. A. Wallace, J. M. Watts, and S. R. Yool, "Characterizing the spatial structure of vegetation communities in the Mojave Desert using geostatistical techniques," Comput. Geosci. 26(4), 397-410 (2000), http://dx.doi.org/10.1016/S0098-3004(99)00120-X.
17. R. G. Craig, "Autocorrelation in Landsat data," in Proc. 13th International Symposium on Remote Sensing of Environment, Ann Arbor, pp. 1517-1524 (1979).
18. P. M. Atkinson, E. Pardo-Igúzquiza, and M. Chica-Olmo, "Downscaling cokriging for super-resolution mapping of continua in remotely sensed images," IEEE Trans. Geosci. Rem. Sens. 46(2), 573-580 (2008), http://dx.doi.org/10.1109/TGRS.2007.909952.
19. M. J. Pringle, M. Schmidt, and J. S. Muir, "Geostatistical interpolation of SLC-off Landsat ETM +images," ISPRS J. Photogram. Rem. Sens. 64(6) 654-664 (2009), http://dx.doi.org/10.1016/j.isprsjprs.2009.06.001.
20. F. Chica-Olmo and M. Abarca-Hernandez, "Radiometric coregionalization of Landsat TM and SPOT HRV images," Int. J. Rem. Sens. 19(5), 997-1005 (1998), http://dx.doi.org/10.1080/014311698215838.
21. M. A. Oliver, R. Webster, and K. Slocum, "Filtering SPOT imagery by kriging analysis," Int. J. Rem. Sens. 21 (4), 735-752 (2000), http://dx.doi.org/10.1080/014311600210542.
22. N. A. C. Cressie, Statistics for Spatial Data, John Wiley & Sons, New York (1993).
23. A. J. Plaza and C. I. Chang, High Performance Computing in Remote Sensing, Chapman & Hall/CRC Computer, Boca Raton (2008).
24. A. Cortés, "Half-duplex dynamic data driven application system for forest fire spread prediction," in Lecture Notes in Computer Science. High Performance Computing and Applications, Vol. 5938, pp. 1-7, Springer (2010).
25. L. S. R. Froude, "Storm tracking with remote data and distributed computing," Comput. Geosci. 34(11), 1621-1630 (2008), http://dx.doi.org/10. 1016/j.cageo.2007.11.004.
26. J. Le Moigne, W. J. Campbell, and R. F. Cromp, "An automated parallel image registration technique based on the correlation of wavelet features," IEEE Trans. Geosci. Rem. Sens. 40(8), 1849-1864 (2002), http://dx.doi.org/10.1109/TGRS.2002.802501.
27. M. K. Dhodhi et al., "D-ISODATA: a distributed algorithm for unsupervised classification of remotely sensed data on network of workstations," J. Parallel Distributed Comput. 59(2), 280-301 (1999), http://dx.doi.org/10.1006/jpdc.1999.1573.
28. S. Wang et al., "Simple grid toolkit: enabling geosciences gateways to cyberinfrastructure," Comput. Geosci. 35(12), 2283-2294 (2009), http://dx.doi.org/10.1016/j.cageo.2009.05.002.
29. National Aeronautics and Space Administration (NASA), Landsat Program http://landsat.gsfc.nasa.gov.
30. A. C. Newton et al., "Remote sensing and the future of landscape ecology," Prog. Phys. Geogr. 33(4), 528-546 (2009), http://dx.doi.org/10. 1177/0309133309346882.
31. X. Pons et al., "Ten years of local water resource management: integrating satellite remote sensing and geographical information systems," Eur. J. Rem. Sens. 45 (1), 317-332 (2012), http://dx.doi.org/10.5721/ EuJRS20124528.
32. L. Martínez et al., "Atmospheric correction algorithm applied to CASI multi-height hyperspectral imagery," in Proc. RAQRS II Valencia, pp. 170-173 (2006).
33. R. E. Wolfe, D. P. Roy, and E. Vermote, "MODIS land data storage, gridding, and compositing methodology: level 2 grid," IEEE Trans. Geosci. Rem. Sens. 36(4), 1324-1338 (1998), http://dx.doi.org/10.1109/36.701082.
34. X. Pons, "MiraMon. Geographical information system and remote sensing software," Center for Ecological Research and Forestry Applications, CREAF, (2000), http://www.creaf.uab.cat/MiraMon (7 January 2013).
35. V. Palà and X. Pons, "Incorporation of relief into geometric corrections based on polynomials," Photogram. Eng. Rem. Sens. 61(7), 935-944 (1995).
36. X. Pons and L. Solé-Sugrañes, "A simple radiometric correction model to improve automatic mapping of vegetation from multispectral satellite data," Rem. Sens. Environ. 48(2), 191-204 (1994), http://dx.doi.org/10.1016/0034-4257(94)90141-4.
37. http://opengis.uab.cat/wms/satcat/index.htm (7 January 2013).
38. A. Zabala et al., "JPEG2000 encoding of images with NODATA regions for remote sensing applications," J. Appl. Rem. Sens. 4(1), 041793 (2010), http://dx.doi.org/10.1117/1.3474978.
39. R. Alamús, J. Talaya, and I. Colomina, "The SISA/0: ICC experiences in airborne sensor integration," in Joint Workshop of ISPRS WG I/1, I/3 and IV/4, Hannover (1999).
40. Warehouse Inventory Search Tool, National Aeronautics and Space Administration (NASA), https://wist.echo.nasa.gov/wist-bin/api/ims.cgi?mode= MAINSRCH&JS=1 (26 May 2011).
41. http://www.kakadusoftware.com (7 January 2013).
42. JPEG2000 Part I: ISO/IEC/15444-1:2004, Part II: ISO/IEC/15444-2:2004, Part III: ISO/IEC/15444-3:2004, Geneva, Switzerland (2004).
43. F. Aulí-Llinàs et al., "J2K: introducing a novel JPEG 2000 coder," Proc. SPIE 5960, 1763-1773 (2005), http://dx.doi.org/10.1117/ 12.633226.
44. P. Goovaerts, Geostatistics for Natural Resources Evaluation, Oxford University Press, New York (1997).
45. G. Matheron, Traité de Géostatistique Appliquée, Editions Technip, Paris (1962).
46. M. A. Oliver and R. Webster, "Kriging: a method of interpolation for geographical information systems," Int. J. Geograph. Inf. Sci. 4(3), 313-332 (1990), http://dx.doi.org/10.1080/02693799008941549.
47. C. E. Woodcock, A. H. Strahler, and D. L. B. Jupp, "The use of variograms in remote sensing: I. Scene models and simulated images," Rem. Sens. Environ. 25(3), 323-348 (1988), http://dx.doi.org/10.1016/0034-4257(88) 90108-3.
48. C. D. Lloyd, Local Models for Spatial Analysis, CRC Press, Boca Raton (2007).
49. L. Pesquer, A. Cortés, and X. Pons, "Parallel ordinary kriging interpolation incorporating automatic variogram fitting," Comput. Geosci. 37(4), 464-473 (2011), http://dx.doi.org/10.1016/j.cageo.2010.10.010.
50. Anonymous, " Introduction to MPI," Int. J. Supercomput. Appl. High Perform. Comput. 8(3- 4), 169-173 (1994), http://dx.doi.org/10.1177/ 109434209400800302.
51. I. Foster, Designing and Building Parallel Programs. Concepts and Tools for Parallel Software Engineering, Addison-Wesley (1995).
52. P. Treitz and P. Howarth, "High spatial resolution remote sensing data for forest ecosystem classification: an examination of spatial scale," Rem. Sens. Environ. 72(3), 268-289 (2000), http://dx.doi.org/10.1016/S0034- 4257(99)00098-X.
53. M. Casas, R. Badia, and J. Labarta, "Automatic analysis of speedup of MPI applications," in Proc. of the 22nd ACM International Conf. on Supercomputing, Island of Kos, Greece, pp. 349-358 (2008).