Classification of filtered multichannel images

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 7830, Issue , 2010, Pages

  Fevralev, Dmitriy V ^a   Lukin, Vladimir V ^a   Ponomarenko, Nikolay N ^a   Vozel, Benoit ^b   Chehdi, Kacem ^b   Kurekin, Andriy ^c   Shark, Lik Kwan ^d  

^a NATIONAL AEROSPACE UNIVERSITY   (Ukraine)

^b UNIVERSITÉ DE RENNES 1   (France)

^c PLYMOUTH MARINE LABORATORY   (United Kingdom)

^d UNIVERSITY OF CENTRAL LANCASHIRE   (United Kingdom)

Author keywords

classification; filtering; multichannel remote sensing data; noise

Indexed keywords

CLASSIFICATION; CLASSIFICATION RESULTS; COMPONENTWISE; DE-NOISING; FILTERING; LANDSAT; MULTICHANNEL IMAGES; MULTICHANNEL REMOTE SENSING DATA; MULTICHANNEL SYSTEM; NOISE; PRE-FILTERING; RADIAL BASIS FUNCTION NEURAL NETWORKS; TEST IMAGES; VISUAL QUALITIES;

COSINE TRANSFORMS; DISCRETE COSINE TRANSFORMS; IMAGE SEGMENTATION; NEURAL NETWORKS; NOISE POLLUTION CONTROL; RADIAL BASIS FUNCTION NETWORKS; REMOTE SENSING; SIGNAL PROCESSING;

THREE DIMENSIONAL;

EID: 78649741308     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.864215     Document Type: Conference Paper

References (45)

1. Hyperspectral Data Exploitation: Theory and Applications, Edited by Chein-I Chang, Wiley-Interscience, 2007.
2. G.P. Kulemin, A.A. Zelensky, J.T. Astola et al, Methods and Algorithms for Pre-processing and Classification of Multichannel Radar Remote Sensing Images, TICSP Series #28, Dec. 2004, ISBN 952-15-1293-8, Tampere, Finland, TTY Monistamo, 116 p.
3. C. Oliver, S. Quegan, Understanding Synthetic Aperture Radar Images, SciTech Publishing, 2004.
4. A. Barducci, D. Guzzi, P. Marcoionni, and I. Pippi, CHRIS-Proba performance evaluation: signal-to-noise ratio, instrument efficiency and data quality from acquisitions over San Rossore (Italy) test site, Proceedings of the 3-rd ESA CHRIS/Proba Workshop, Italy, 11 p., March 2005.
5. J.P. Kerekes, J.E. Baum, Hyperspectral Imaging System Modeling, Lincoln Laboratory Journal, Vol. 14, No 1, 2003, pp. 117-130.
6. Lukin V.V., Astola J.T., Melnik V.P., Kurekin A.A., Zelensky A.A., Kulemin G.P., Ponomarenko N.N., Dolia A.N., Parkkinen J. Data Fusion and Processing for Airborne Multichannel System of Radar Remote Sensing: Methodology, Stages and Algorithms, Proceedings of AeroSense'2000, Orlando (USA), April 2000, pp. 215-227.
7. U. Amato, R.M. Cavalli, A. Palombo, S. Pignatti, F. Santini, Experimental approach to the selection of the components in the minimum noise fraction, IEEE Transactions on Geoscience and Remote Sensing, 47, No 1, pp. 153-160, 2009.
8. S. De Backer, A. Pizurica, B. Huysmans, W. Philips, P. Scheunders, Denoising of multicomponent images using wavelet least squares estimators, Image and Vision Computing, Vol. 26, No 7, 2008, pp. 1038-1051.
9. A. Zabala, X. Pons, R. Diaz-Delgado, F. Garcia, F. Auli-Llinas, J. Serra-Sagrista, Effects of JPEG and JPEG2000 lossy compression on remote sensing image classification for mapping crops and forest areas, Proceedings of IGARSS, pp. 790-793, 2006.
10. Smolka B., Plataniotis K.N., Venetsanopoulos A.N., Nonlinear Techniques for Color Image Processing, Chapter 12 in Nonlinear Signal and Image Processing: Theory, Methods, and Applications, Electrical Engineering & Applied Signal Processing Series, ed. by K. Barner and G. Arce, CRC Press, 2003, 560 p.
11. Foi A., M. Trimeche, Katkovnik V., Egiazarian K. Practical Poissonian-Gaussian Noise Modeling and Fitting for Single Image Raw Data, IEEE Transactions on Image Processing, 17, No 10, 2007, pp. 1737-1754.
12. N. Ponomarenko, V. Lukin, K. Egiazarian, J. Astola, M. Carli, F. Battisti, Color Image Database For Evaluation Of Image Quality Metrics, IEEE Signal Processing Society 2008 International Workshop on Multimedia Signal Processing, Australia, Sept 2008, pp.403-408.
13. Z. Wang, A.C. Bovik, Mean squared error: love it or leave it? A new look at image fidelity measures, IEEE Signal Processing Magazine, Jan. 2009, pp. 98-117.
14. Christophe, E., Leger, D., and Mailhes, C., Quality criteria benchmark for hyperspectral imagery, IEEE Transactions on Geoscience and Remote Sensing, 43(9), pp. 2103-2114, 2005.
15. Lukin V., Ponomarenko N., Zelensky A., Astola J., Egiazarian K. Automatic Design of Locally Adaptive Filters for Pre-processing of Images Subject to Further Interpretation, Proceedings of 2006 IEEE Southwest Symposium on Image Analysis and Interpretation, Denver, USA, 2006, pp. 41-45.
16. Touzi R., A Review of Speckle Filtering in the Context of Estimation Theory, IEEE Transactions on Geoscience and Remote Sensing, 40, No 11, 2002, pp. 2392-2404.
17. A. Hyvarinen, P. Hoyer, E. Oja, Image Denoising by Sparse Code Shrinkage, In Intelligent Signal Processing, ed. By S. Haykin and B. Kosko, IEEE Press, 2001.
18. F. Argenti, G. Torricelli, L. Alparone, Signal dependent noise removal in the undecimated wavelet domain, Proceedings of ICASSP, 2002, pp. 3293-3296.
19. K. Dabov, A. Foi, V. Katkovnik, and K. Egiazarian, Image denoising by sparse 3D transform-domain collaborative filtering, IEEE Transactions on Image Processing, 16, No 8, August 2007, pp. 2080-2095.
20. D.D. Muresan, T.W. Parks, Adaptive Principal Components and Image Denoising, Proceedings of ICIP, 2003, I, pp. 101-104.
21. J.S. Lee, J.H. Wen, T.I. Ainsworth, K.S. Chen, A.J. Chen, Improved Sigma Filter for Speckle Filtering of SAR Imagery, IEEE Transactions on Geoscience and Remote Sensing, 47, No 1, Jan. 2009, pp. 202-213.
22. V.V. Lukin, N.N. Ponomarenko, S.K. Abramov, B. Vozel, K. Chehdi, J. Astola, Filtering of radar images based on blind evaluation of noise characteristics, Proceedings of Image and Signal Processing for Remote Sensing XIV, Cardiff, UK, Sept 2008, SPIE 7109, 12 p.
23. Astola J., Haavisto P. and Neuvo Y., Vector median filters, Proceedings of IEEE, 1990, Vol. 78, pp. 678-689.
24. Kurekin A.A., Lukin V.V., Zelensky A.A., Koivisto P.T., Astola J.T., Saarinen K.P., Comparison of component and vector filter performance with application to multichannel and color image processing, Proceedings of the IEEE-EURASIP Workshop on Nonlinear Signal and Image Processing, June 1999, Antalya, Turkey, 1, pp. 38-42.
25. N.N. Ponomarenko, V.V. Lukin, A.A. Zelensky, P.T. Koivisto, K.O. Egiazarian, 3D DCT Based Filtering of Color and Multichannel Images, Telecommunications and Radio Engineering, 67, 2008, pp. 1369-1392.
26. Carton-Vandecandelaere M.-P., Vozel B., Klaine L., Chehdi K., Application to Multispectral Images of a Blind Identification System for Blur, Additive, Multiplicative and Impulse Noises. Proceedings of EUSIPCO, III, 2002, pp. 283-286.
27. Vozel B., Abramov S., Chehdi K., Lukin V., Ponomarenko N., Uss M., Blind methods for noise evaluation in multi-component images, Book chapter in Multivariate Image Processing, France, 2009, pp. 263-301.
28. C. Liu, W. T. Freeman, R. Szeliski, and S. B. Kang, Noise estimation from a single image, Proceedings of IEEE Conf. Computer Vision and Patter Recognition, pp. 901-908, June 2006.
29. M. Mäkitalo, A. Foi, On the inversion of the Anscombe transformation in low-count Poisson image denoising, Proceedings of International Workshop on Local and Non-Local Approximations in Image Processing, LNLA 2009, Tuusula, Finland, pp. 26-32, Aug. 2009.
30. Foi A., Direct optimization of nonparametric variance-stabilizing transformations, presented at 8emes Rencontres de Statistiques MathÈmatiques, CIRM, Luminy, December 2008.
31. Tsymbal O.V., Lukin V.V., Ponomarenko N.N., Zelensky A.A., Egiazarian K.O., Astola J.T., Three-state Locally Adaptive Texture Preserving Filter for Radar and Optical Image Processing, EURASIP Journal on Applied Signal Processing, No 8, pp. 1185-1204, May 2005.
32. R. Oktem, K. Egiazarian, V. Lukin, N. Ponomarenko, O. Tsymbal, Locally Adaptive DCT Filtering for Signal- Dependent Noise Removal, EURASIP Journal on Advances in Signal Processing, Article ID 42472, 10 p., 2007.
33. V.V. Lukin, R. Oktem, N. Ponomarenko, K. Egiazarian, Image filtering based on discrete cosine transform, Telecommunications and Radio Engineering, 66, No 18, pp. 1685-1701, 2007.
34. V. Lukin, N. Ponomarenko, K. Egiazarian, J. Astola, Adaptive DCT-based filtering of images corrupted by spatially correlated noise, Proceedings of SPIE Conference Image Processing: Algorithms and Systems VI, SPIE 6812, 12 p., 2008.
35. Kurekin A.A., Lukin V.V., Zelensky A.A., Astola J.T., Koivisto P.T., Modified vector sigma filter and its application to color and multichannel remote sensing radar image processing, Proceedings of SPIE Conference on Applications of Digital Image Processing, SPIE 3808, Denver, July 1999, 9 p.
36. D. Fevralev, S. Krivenko, V. Lukin, A. Zelensky, K. Egiazarian, Speeding-up DCT based Filtering of Images, CD ROM Proceedings of the International Conference "Modern Problems of Radioengineering, Telecommunications and Computer Science" (TCSET), Lviv-Slavsko, Ukraine, Feb. 2010, 6 p.
37. D. Fevralev, V. Lukin, S. Krivenko, N. Ponomarenko, A. Kurekin, Classification of DCT based Filtered Multichannel Images, CD ROM Proceedings of the International Conference "Modern Problems of Radioengineering, Telecommunications and Computer Science" (TCSET), Lviv-Slavsko, Ukraine, Feb. 2010, p. 311-319.
38. N.K. Bose, P. Liang, Neural network fundamentals with graphs, algorithms and applications, McGraw Hill, 1996.
39. Schölkopf, B., Burges, J.C., Smola, A.J., Advances in Kernel Methods: Support Vector Learning, MIT Press, Cambridge, MA, 1999.
40. N. Ponomarenko, F. Silvestri, K. Egiazarian, M. Carli, J. Astola, V. Lukin, On between-coefficient contrast masking of DCT basis functions, CD-ROM Proceedings of the Third International Workshop on Video Processing and Quality Metrics, USA, 2007, 4 p.
41. R.R. Coifman, D.L. Donoho, Translation-invariant denoising, in: A. Antoniadis, G. Oppenheim (Eds.), Wavelets and Statistics, Lecture Notes, Springer, Berlin, Germany, 1995, pp. 125-150.
42. E.P. Simoncelli, E.H. Adelson, Noise removal via Bayesian wavelet coring, Proceedings of ICIP, 1, pp. 379-382, 1996.
43. Wang Z., Simoncelli E.P., Bovik A.C., Multi-scale Structural Similarity for Visual Quality Assessment, Proceedings of the 37th IEEE Asilomar Conference on Signals, Systems and Computers, 2, pp. 1398-1402, 2003.
44. N. Cristianini, J. Shawe-Taylor. An Introduction to Support Vector Machines and Other Kernel-based Learning Methods. Cambridge University Press, 2000.
45. V.V. Lukin, N.N. Ponomarenko, A.A. Zelensky, A.A. Kurekin, K. Lever, Classification of compressed multichannel remote sensing images, Proceedings of SPIE/EUROPTO on Remote Sensing, UK, Sept 2008, SPIE 7109, 12 p.