Hyperspectral remote sensing data compression and protection
M.V. Gashnikov, N.I. Glumov, A.V. Kuznetsov, V.A. Mitekin, V.V. Myasnikov, V.V. Sergeev


Image Processing Systems Institute оf RAS – Branch of the FSRC “Crystallography and Photonics” RAS, Samara, Russia,
Samara National Research University, Samara, Russia

Full text of article: English language.


In this paper, we consider methods for hyperspectral image processing, required in systems of image formation, storage, and transmission and aimed at solving problems of data compression and protection. A modification of the digital image compression method based on a hierarchical grid interpolation is proposed. Methods of active (on the basis of digital watermarking) and passive (on the basis of artificial image distortion detection) data protection against unauthorized dissemination are developed and investigated.

digital image processing, image analysis, hyperspectral images, data compression, hierarchical grid interpolation method, digital watermarks.

Gashnikov MV, Glumov NI, Kuznetsov AV, Mitekin VA, Myasnikov VV, Sergeev VV. Hyperspectral remote sensing data compression and protection. Computer Optics 2016; 40(5): 689-712. DOI: 10.18287/2412-6179-2016-40-5-689-712.


  1. Chang C-I. Hyperspectral Data Processing: Algorithm Design and Analysis. Hoboken, NJ: Wiley Press; 2013. ISBN: 978-0-471-69056-6.
  2. Schowengerdt RA. Remote Sensing – Models and Methods for Image Processing. 2nd ed. London, San Diego: Academic Press; 1997. ISBN: 0-12-628981-6.
  3. Chang C-I. Hyperspectral imaging: techniques for spectral detection and classification. New York: Springer; 2003. ISBN: 978-0-306-47483-5. DOI: 10.1007/978-1-4419-9170-6.
  4. Borengasser M, Hungate WS, Watkins R. Hyperspectral Remote Sensing – Principles and Applications. Boca Raton, FL: CRC Press; 2004. ISBN: 978-1-566-70654-4.
  5. Chang C-I, ed. Hyperspectral data exploitation: theory and applications. Wiley-Interscience; 2007. ISBN: 978-0-471-74697-3. DOI: 10.1002/9780470124628.ch3.
  6. Gashnikov MV, Glumov NI, Myasnikov VV, Chernov AV, Ivanova EV. Regional Geographic Information Systems for Gas Network Monitoring. Pattern Recognition and Image Analysis 2015; 25(3): 418-422. DOI: 10.1134/S1054661815030062.
  7. Chanussot J, Crawford M, Kuo B. Foreword to the Special Issue on Hyperspectral Image and Signal Processing. IEEE Transactions on Geoscience and Remote Sensing 2010; 48(11): 3871-3876. DOI: 10.1109/TGRS.2010.2085313.
  8. Chang C-I, Chiang SS. Anomaly detection and classification for hyperspectral imagery. IEEE Transactions on Geoscience and Remote Sensing 2002; 40(6): 1314-1325. DOI: 10.1109/TGRS.2002.800280.
  9. Benz U, Hofmann P, Willhauck G, Lingenfelder I, Heynen M. Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information. ISPRS Journal of Photogrammetry and Remote Sensing 2004; 58(3): 239-258. DOI: 10.1016/j.isprsjprs.2003.10.002.
  10. Gashnikov MV, Glumov NI. Hierarchical compression for hyperspectral image storage [In Russian]. Computer Optics 2014; 38(3): 482-488.
  11. Gashnikov MV, Glumov NI. Hyperspectral images repository using a hierarchical compression. 23-rd International Conference on Computer Graphics, Visualization and Computer Vision proceeding 2015; 1-4. ISBN: 978-80-86943-67-1. ISSN: 2464-4617.
  12. Salomon D. Data Compression. The Complete Reference. 4th ed. London: Springer-Verlag; 2007. ISBN: 978-1-84628-602-5. DOI: 10.1007/978-1-84628-603-2.
  13. Vatolin D, Ratushnyak A, Smirnov M, Yukin V. Data compression methods. Archive program architecture, image and video compression [In Russian]. Moscow: “DIALOG-MIFI” Publisher; 2002.
  14. Pratt WK. Digital image processing: PIKS Scientific Inside. 4th ed. John Wiley & Sons, Inc.; 2007. ISBN: 978-0-471-76777-0. DOI: 10.1002/0470097434.
  15. Soifer VA, ed, Chernov AV, Chernov VM, Chicheva MA, Fursov VA, Gashnikov MV, Glumov NI, Ilyasova NY, Khramov AG, Korepanov AO, Kupriyanov AV, Myasnikov EV, Myasnikov VV, Popov SB, Sergeyev VV. Computer Image Processing, Part II: Methods and algorithms. VDM Verlag; 2010. ISBN: 978-3-639-17545-5.
  16. Gashnikov MV. Parameterization of nonlinear Greham predictor for digital image compression [In Russian]. Computer Optics 2016; 40(2): 225-231. DOI: 10.18287/2412 -6179-2016-40-2-225-231.
  17. Woods E, Gonzalez R. Digital Image Processing. 3rd ed. Prentice Hall; 2007. ISBN: 978-0-131-68728-8.
  18. Wallace G. The JPEG Still Picture Compression Standard. Communications of the ACM 1991; 34(4): 30-44. DOI: 10.1145/103085.103089.
  19. Sridevi M, Mala C, Sanyam S. Comparative study of image forgery and copy-move techniques. Second International Conference on Computer Science, Engineering and Applications (ICCSEA 2012). New Delhi, India; 2012: 715-723.
  20. Lossless Multispectral & Hyperspectral Image Compression. Recommendation for Space Data System Standards, CCSDS 123.0-B-1. Blue Book; 1. Washington, D.C.: CCSDS, 2012.
  21. Nian Y, He M, Wan J. Lossless and near-lossless compression of hyperspectral images based on distributed source coding. Journal of Visual Communication and Image Representation 2015; 28: 113-119. DOI: 10.1016/j.jvcir.2014.06.008.
  22. Valsesia D, Magli E. A novel rate control algorithm for onboard predictive coding of multispectral and hyperspectral images. IEEE Trans. Geosci. Remote Sens. 2014; 52(10): 6341-6355. DOI: 10.1109/TGRS.2013.2296329.
  23. Multispectral Hyperspectral Data Compression Working Group. Source: <http://cwe.ccsds.org/sls/default.aspx>.
  24. Consultative Committee for Space Data Systems (CCSDS). Source: < http://www.ccsds.org >.
  25. Gashnikov MV, Glumov NI, Sergeyev VV. The image compression method in real-time remote sensing [In Russian]. 9th All-Russian conference “Mathematical methods of pattern recognition”, Moscow, 1999: 160-163.
  26. Gashnikov MV, Glumov NI, Sergeyev VV. Compression Method for Real-Time Systems of Remote Sensing. 15th International Conference on Pattern Recognition 2000 (Barselona); 3: 232-235. DOI: 10.1109/ICPR.2000.903527.
  27. Gashnikov MV, Glumov NI. Hierarchical grid interpolation for hyperspectral image compression [In Russian]. Computer Optics 2014; 38(1): 87-93.
  28. Gashnikov MV, Glumov NI. Hierarchical GRID Interpolation under Hyperspectral Images Compression. Optical Memory and Neural Networks (Information Optics) 2014; 23(4): 246-253. DOI: 10.3103/S1060992X14040031.
  29. Gashnikov MV, Glumov NI, Sergeev VV. A hierarchical compression method for space images. Automation and Remote Control 2010; 71(3): 501-513. DOI: 10.1134/S0005117910030112.
  30. Gashnikov MV, Glumov NI. Onboard processing of hyperspectral data in the remote sensing systems based on hierarchical compression. Computer Optics 2016; 40(4): 543-551. DOI: 10.18287/2412-6179-2016-40-4-543-551.
  31. Glumov NI. Improving Noise Immunity of Transmission of Compressed Digital Images. Pattern Recognition and Image Analysis, 2003; 13(2): 273-276.
  32. Lin S, Costello D. Error Control Coding: Fundamentals and Applications, second edition. New Jersey: Prentice-Hall, inc. Englewood Cliffs; 2004. ISBN: 978-0-130-42672-7.
  33. SpecTIR data – Advanced hyperspectral and geospatial solutions. Corporate headquarters SpecTIR remote sensing. Source: <http://www.spectir.com/free-data-samples>.
  34. AVIRIS data – ordering free AVIRIS standard data products. Jet propulsion laboratory. Source:< http://aviris.jpl.nasa.gov/data/free_data.html>.
  35. Kbaier I, Belhadj Z. A novel content preserving watermarking scheme for multipectral images. Information and Communication Technologies (ICTTA'06, 2nd) 2006; 1: 322-327. DOI: 10.1109/ICTTA.2006.1684390.
  36. Minguillón J. Evaluation of copyright protection schemes for hyperspectral imaging. Remote Sensing. International Society for Optics and Photonics 2004: 512-523. DOI: 10.1117/12.511161.
  37. Jing L, Zhang Y, Chen G. Zero-watermarking for copyright protection of remote sensing image. Signal Processing (ICSP 2008. 9th International Conference on) 2008: 1083-1086. DOI: 10.1109/ICOSP.2008.4697317.
  38. Wang X, Guan Z, Wu C. A novel information hiding technique for remote sensing image. In: Proceeding ADMA'05 Proceedings of the First international conference on Advanced Data Mining and Applications 2005: 423-430. DOI: 10.1007/11527503_51.
  39. Kaarna A, Toivanen P. Digital watermarking of spectral images in PCA/Wavelet-transform domain. Geoscience and Remote Sensing Symposium (IGARSS'03) Proceedings 2003; 6: 3564-3567. DOI: 10.1109/IGARSS.2003.1294855.
  40. Kaarna A, Parkkinen J. Digital watermarking of spectral images with three-dimensional wavelet transform. In book: Image Analysis. Proceedings of the 13th Scandinavian Conference, SCIA 2003 Halmstad, Sweden, June 29 – July 2, 2003: 320-327. DOI: 10.1007/3-540-45103-X_44.
  41. Melgani F, Benzid R, De Natale F. Near-lossless spread spectrum watermarking for multispectral remote sensing images. J Appl Remote Sens 2007; 1(1): 013501. DOI: 10.1117/1.2535355.
  42. Panyavaraporn J, Rangsanseri Y. Digital Image-in-Image Watermarking of Remote Sensing Images. 26th Asian Conference on Remote Sensing and 2nd Asian Space Conference ACRS2005 2005; 1: 1145-1150.
  43. Barni MF, Bartolinib F, Cappellinib V, Maglic E, Olmoc G. Near-lossless digital watermarking for copyright protection of remote sensing images. Geoscience and Remote Sensing Symposium (IGARSS '02) 2002; 3: 1447-1449. DOI: 10.1109/IGARSS.2002.1026144.
  44. Doërr G, Dugelay JL. Security pitfalls of frame-by-frame approaches to video watermarking. IEEE Transactions on Signal Processing 2004; 52(10): 2955-2964. DOI: 10.1109/TSP.2004.833867.
  45. Lin ET, Delp EJ. A review of fragile image watermarks. Proceedings of the Multimedia and Security Workshop (ACM Multimedia '99) Multimedia Contents, October 1999, Orlando 1999; 1: 25-29.
  46. Tirkel AZ, Hall TE. A unique watermark for every image. IEEE Multimedia 2001; 8(4): 30-37. DOI: 10.1109/93.959098.
  47. Van Schyndel RG, Tirkel AZ, Svalbe ID. Key independent watermark detection. IEEE International Conference on Multimedia Computing and Systems 1999; 1: 580-585. DOI: 10.1109/MMCS.1999.779265.
  48. Van Schyndel RG, Tirkel AZ, Svalbe ID, Hall TE, Osborne CF. Spread-Spectrum Digital Watermarking Concepts and Higher Dimensional Array Constructions. First International Online Symposium on Electronics Engineering 2000: 1-13.
  49. Van Schyndel RG, Tirkel AZ, Svalbe ID, Hall TE, Osborne CF. Algebraic construction of a new class of quasi-orthogonal arrays for steganography. Proc SPIE 1999; 3657: 354-364. DOI: 10.1117/12.344685.
  50. Chen L, Gong G. Communication system security. Boca Raton, FL: CRC Press; 2012. ISBN: 978-1-439-84036-8.
  51. Mitekin VA, Timbay EI. A new watermarking sequence generation algorithm for collision-free digital watermarking. Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP) Eighth International Conference on 2012: 256-260. DOI: 10.1109/IIH-MSP.2012.68.
  52. Mitekin VA, Fedoseev VA. A new method for high-capacity information hiding in video robust against temporal desynchronization. Proc SPIE 2015; 9445: 94451A. DOI: 10.1117/12.2180550.
  53. Mahdian B, Saic S. A bibliography on blind methods for identifying image forgery. Signal Processing: Image Communication 2010; 25(6): 389-399. DOI: 10.1016/j.image.2010.05.003.
  54. Fridrich J, Soukal D, Lukas J. Detection of copy–move forgery in digital images. Proceedings of Digital Forensic Research Workshop, Cleveland 2003: 55-61.
  55. Mahdian B, Saic S. A cyclostationarity analysis applied to image forensics. IEEE Workshop on Applications of Computer Vision (IEEE WACV), Snowbird 2009: 1-6. DOI: 10.1109/WACV.2009.5403088.
  56. Farid H. Exposing digital forgeries from JPEG ghosts. IEEE Transactions on Information Forensics and Security 2009; 4(1): 154-160. DOI: 10.1109/TIFS.2008.2012215.
  57. Ng TT. Camera response function signature for digital forensics – Part II: Signature extraction. IEEE Workshop on Information Forensics and Security 2009: 161-165. DOI: 10.1109/WIFS.2009.5386461.
  58. Popescu AC, Farid H. Exposing digital forgeries by detecting traces of re-sampling. IEEE Transactions on Signal Processing 2005; 53(2): 758-767. DOI: 10.1109/TSP.2004.839932.
  59. Poilpré MC, Perrot P, Talbot H. Image tampering detection using Bayer interpolation and JPEG compression. Proceedings of the 1st International Conference on Forensic Applications and Techniques in Telecommunications, Information, and Multimedia Workshop 2008: 1-5.
  60. Bayram S, Sencar HT, Memon N. A survey of copy-move forgery detection techniques. Proceedings of the IEEE Western New York Image Processing Workshop 2009: 538-542.

© 2009, IPSI RAS
Institution of Russian Academy of Sciences, Image Processing Systems Institute of RAS, Russia, 443001, Samara, Molodogvardeyskaya Street 151; e-mail: ko@smr.ru; Phones: +7 (846) 332-56-22, Fax: +7 (846) 332-56-20