Abstract
The performance of an image processing algorithm can be assessed through its resulting images. However, in order to do so, both ground truth image and noisy target image with known properties are typically required. In the context of hyperspectral image processing, another constraint is introduced, i.e. apart from its mathematical properties, an artificial signal, noise, or variations should be physically correct. Deciding to work in an intermediate level, between real spectral images and mathematical model of noise, we develop an approach for obtaining suitable spectral impulse signals. The model is followed by construction of target images corrupted by impulse signals and these images will later on be used to evaluate the performance of a filtering algorithm.
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Norsk Elektro Optikk AS: HySpex. http://www.neo.no/hyspex/
Alajlan, N., Jernigan, E.: An effective detail preserving filter for impulse noise removal. In: Campilho, A.C., Kamel, M.S. (eds.) ICIAR 2004. LNCS, vol. 3211, pp. 139–146. Springer, Heidelberg (2004)
Astola, J., Haavisto, P., Neuvo, Y.: Vector median filters. Proceedings of the IEEE 78(4), 678–689 (1990)
Bar, L., Brook, A., Sochen, N., Kiryati, N.: Color image deblurring with impulsive noise. In: Paragios, N., Faugeras, O., Chan, T., Schnörr, C. (eds.) VLSM 2005. LNCS, vol. 3752, pp. 49–60. Springer, Heidelberg (2005)
Celebi, M.E., Kingravi, H.A., Aslandogan, Y.A.: Nonlinear vector filtering for impulsive noise removal from color images. Journal of Electronic Imaging 16(3), 033008-1–033008-21 (2007)
Chan, R., Ho, C.W., Nikolova, M.: Salt-and-pepper noise removal by median-type noise detectors and detail-preserving regularization. IEEE Transactions on Image Processing 14(10), 1479–1485 (2005)
Justusson, B.J.: Median filtering: Statistical properties. Two Dimensional Digital Signal Processing 2, 161–196 (1981)
Kober, V., Mozerov, M., Álvarez-Borrego, J.: Automatic removal of impulse noise from highly corrupted images. In: Sanfeliu, A., Cortés, M.L. (eds.) CIARP 2005. LNCS, vol. 3773, pp. 34–41. Springer, Heidelberg (2005)
Nair, M.S., Revathy, K., Tatavarti, R.: Removal of salt-and pepper noise in images: a new decision-based algorithm. In: Proceedings of the International MultiConference of Engineers and Computer Scientists (IMECS) I, pp. 19–21 (2008)
Nowicki, K.J., Edwards, C.S., Christensen, P.R.: Removal of salt-and-pepper noise in THEMIS infrared radiance and emissivity spectral data of the martian surface. IEEE-Whispers Transactions (2013, in press)
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Deborah, H., Richard, N., Hardeberg, J.Y. (2015). Spectral Impulse Noise Model for Spectral Image Processing. In: Trémeau, A., Schettini, R., Tominaga, S. (eds) Computational Color Imaging. CCIW 2015. Lecture Notes in Computer Science(), vol 9016. Springer, Cham. https://doi.org/10.1007/978-3-319-15979-9_17
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DOI: https://doi.org/10.1007/978-3-319-15979-9_17
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