Fusion of sensor data, knowledge sources and algorithms for extraction and classification of topographic objects

baltsavias, emmanuel p.

Bibliographic data

Monograph

Persistent identifier:: 856473650

Author:: Baltsavias, Emmanuel P.

Title:: Fusion of sensor data, knowledge sources and algorithms for extraction and classification of topographic objects

Sub title:: Joint ISPRS/EARSeL Workshop ; 3 - 4 June 1999, Valladolid, Spain

Scope:: III, 209 Seiten

Year of publication:: 1999

Place of publication:: Coventry

Publisher of the original:: RICS Books

Identifier (digital):: 856473650

Illustration:: Illustrationen, Diagramme, Karten

Language:: English

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2016

Document type:: Monograph

Collection:: Earth sciences

Chapter

Title:: INTERACTIVE SESSION 1 IMAGE CLASSIFICATION

Document type:: Monograph

Structure type:: Chapter

Chapter

Title:: ASSESSMENT OF NOISE VARIANCE AND INFORMATION CONTENT OF MULTI-/HYPER-SPECTRAL IMAGERY. Bruno Aiazzi, Luciano Alparone, Alessandro Barducci, Stefano Baronti, Ivan Pippi

Document type:: Monograph

Structure type:: Chapter

International Archives of Photogrammetry and Remote Sensing, Vol. 32, Part 7-4-3 W6, Valladolid, Spain, 3-4 June, 1999 174 SNR (dB) (a) Information parameters (b/pel) (b) Fig. 9. (a) SNR (dB) and (b) information parameters (b/pel) measured for bands 12 to 41 from the test AVIRIS Cuprite Mine ’89 image. h u is the entropy of the esti mated observation noise, h s is the estimated entropy of the noise-free multi-spectral image, r is the code rate. ACKNOWLEDGEMENT This research was carried out under the financial support of the Italian Space Agency (ASI). REFERENCES Aiazzi, B„ Alparone, L., Baronti, S., Borri, G., 1998a. Pyramid- based multiresolution adaptive filters for additive and multiplica tive image noise. IEEE Transactions on Circuits and Systems-II, 45(8), pp. 1092-1097. Aiazzi, B., Alparone, L„ Baronti, S., 1998b. Multiresolution local-statistics speckle filtering based on a ratio Laplacian pyra mid. IEEE Transactions on Geoscience and Remote Sensing, 36(5), pp. 1466-1476. Aiazzi, B., Alparone, L., Baronti S., 1999a. Signal-dependent noise modeling for adaptive multiresolution local-statistics fil tering. In: Nonlinear Image Processing X, E.R. Dougherty, J.T. Astola, (Eds.), Proceedings SPIE 3646, pp. 207-216. entropy matching for generalized Gaussian PDF modeling. IEEE Signal Processing Letters, 6(6), pp. 138-140. Aiazzi, B., Alba R, Alparone, L., Baronti S., 1999c. Lossless compression of multi/hyper-spectral imagery based on a 3-D fuzzy prediction. IEEE Transactions on Geoscience and Remote Sensing, 37(5). Aiazzi, B., Alparone, L., Baronti S., 1999d. Advantages of bidirectional spectral prediction for the reversible compression of multispectral data. In: Proceedings IEEE International Geo science And Remote Sensing Symposium IGARSS’99, Ham burg, Germany, pp. 2043-2045. Amavut, Z., 1998. Permutations and prediction for lossless com pression of multispectral TM images. IEEE Transactions on Geo science and Remote Sensing, 36(3), pp. 999-1003. Barducci, A., Pippi, I., 1998. SNR estimation and systematic dis turbances rejection in hyperspectral remotely sensed images of the Earth. In: Sensors, Systems, and Next-Generation Satellites II, Proceedings EUROPTO Series, Barcelona, Spain, SPIE Vol. 3498, pp. 420-429. Goodman, J.W., 1976. Some fundamental properties of speckle. Journal of the Optical Society of America, 66, pp. 1145-1150. Jayant, N.S., Noll, R, 1984. Digital Coding of Waveforms. Pren tice Hall, Englewood Cliffs, NJ. Kuan, D.T., Sawchuk, A.A., Strand, T.C., Chavel, R, 1985. Adaptive noise smoothing filter for images with signal-dependent noise. ШЕЕ Transactions on Pattern Analysis and Machine Intel ligence, 7(2), pp. 165-177. Memon, N.D., Sayood, K., Magliveras, S.S., 1994. Lossless com pression of multispectral image data. ШЕЕ Transactions on Geo science and Remote Sensing, 32(2), pp. 282-287. Naderi, E, Sawchuk, A.A., 1978. Estimation of images degraded by film-grain noise. Applied Optics, 17, pp. 1228-1237. Rao, A.K., Bhargava, S., 1996. Multispectral data compression using bidirectional interband prediction. ШЕЕ Transactions on Geoscience and Remote Sensing, 34(2), pp. 385-397. Roger, R.E., Cavenor, M.C., 1996a. Lossless compression of AVIRIS images. ШЕЕ Transactions on Image Processing, 5(5), pp. 713-719. Roger, R.E., Arnold, J.F., 1996b. Reliably estimating the noise in AVTRIS hyperspectral images. International Journal of Remote Sensing, 17(10), pp. 1951-1962. Ryan, M.J., Arnold, J.F., 1997. The lossless compression of AVTRIS images by vector quantization. ШЕЕ Transactions on Geoscience and Remote Sensing, 35(3), pp. 546-550. Wang, J., Zhang, K., Tang, S., 1995. Spectral and spatial decorre lation of Landsat-TM data for lossless compression. ШЕЕ Trans actions on Geoscience and Remote Sensing, 33(5), pp. 1277- 1285. Wu, X., Memon, N.D., 1997. Context-based, adaptive, lossless image coding. ШЕЕ Transactions on Communications, 45(4), pp. 437^144. Aiazzi, B., Alparone, L., Baronti S., 1999b. Estimation based on

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