Abstract
LED illumination based multispectral imaging (LEDMSI) is one of the promising techniques of fast and effective spectral image acquisition. Several LEDMSI systems and methodologies have been proposed in the literature. A typical LEDMSI system uses a monochrome camera, which captures images of a scene under n different color LED lights, producing an n-band spectral image of the scene. RGB camera based LEDMSI systems have been proposed to speed up the acquisition process. However, demosaicing process in these systems affects the spatial accuracy, and in turn influences the quality of resulting spectral images. In this paper, we study how the performance and quality of LEDMSI systems are influenced by different factors. Four major factors: camera type, demosaicing, number of color LEDs and, noise are considered in the study. We carry out simulation experiments using monochrome and RGB camera based LEDMSI systems, under the influence of different amounts of noise and practical constraints on the number of different color LEDs. The experiments confirm the influence of these factors on the performance of a LEDMSI system. We believe that this work would be useful not only in designing LEDMSI systems, but also in developing quality framework(s) for the evaluation of spectral images and spectral imaging systems.
Chapter PDF
Similar content being viewed by others
References
Rowe, R., Uludag, U., Demirkus, M., Parthasaradhi, S., Jain, A.: A multispectral whole-hand biometric authentication system. In: Biometrics Symposium, pp. 1–6 (September 2007)
Everdell, N.L., Styles, I.B., Claridge, E., Hebden, J.C., Calcagni, A.S.: Multispectral imaging of the ocular fundus using LED illumination. In: Novel Optical Instrumentation for Biomedical Applications IV, vol. 7371. SPIE Proceedings (2009)
Shrestha, R., Hardeberg, J., Boust, C.: LED based multispectral film scanner for accurate color imaging. In: The 8th International Conference on Signal Image Technology and Internet Based Systems (SITIS), pp. 811–817. IEEE Proceedings (November 2012)
Christens-Barry, W.A., Boydston, K., France, F.G., Knox, K.T., Easton, J. R.L., Toth, M.B.: Camera system for multispectral imaging of documents. In: Sensors, Cameras, and Systems for Industrial/Scientific Applications X, vol. 7249, pp. 724908–724908–10. SPIE Proceedings (2009)
Shrestha, R., Hardeberg, J.Y.: Multispectral imaging using LED illumination and an RGB camera. In: The 21st Color and Imaging Conference (CIC) on Color Science and Engineering Systems, Technologies, and Applications, pp. 8–13. IS&T (2013)
Martinez, O., Vilaseca, M., Arjona, M., Pizarro, C., Pujol, J.: Use of light-emitting diodes in multispectral systems design: Variability of spectral power distribution according to angle and time of usage. Journal of Imaging Science and Technology 55(5), 50501-1–50501-8 (2011)
Shrestha, R., Hardeberg, J.Y.: LED matrix design for multispectral imaging. In: The 12th International AIC Congress, vol. 4, pp. 1317–1320. AIC Proceedings (July 2013)
Park, J.I., Lee, M.H., Grossberg, M.D.D., Nayar, S.K.: Multispectral imaging using multiplexed illumination. In: IEEE International Conference on Computer Vision (ICCV), pp. 1–8 (2007)
Parmar, M., Lansel, S., Farrell, J.: An LED-based lighting system for acquiring multispectral scenes. In: Digital Photography VIII, vol. 82990, pp. 82990P–82990P–8. SPIE Proceedings (January 2012)
Hardeberg, J.Y.: Acquisition and Reproduction of Colour Images: Colorimetric and Multispectral Approaches. Doctoral dissertation, École Nationale Supérieure des Télécommunications de Paris (1999)
Longere, P., Zhang, X., Delahunt, P., Brainard, D.: Perceptual assessment of demosaicing algorithm performance. IEEE Proceedings 90(1), 123–132 (2002)
Hirakawa, K., Parks, T.: Adaptive homogeneity-directed demosaicing algorithm. IEEE Transactions on Image Processing 14(3), 360–369 (2005)
Paliy, D., Katkovnik, V., Bilcu, R., Alenius, S., Egiazarian, K.: Spatially adaptive color filter array interpolation for noiseless and noisy data. International Journal of Imaging Systems and Technology 17(3), 105–122 (2007)
Lu, Y., Karzand, M., Vetterli, M.: Demosaicking by alternating projections: Theory and fast one-step implementation. IEEE Transactions on Image Processing 19(8), 2085–2098 (2010)
University of Eastern Finland, Spectral Color Research Group: Joensuu spectral image database, https://www.uef.fi/spectral/spectral-image-database (last visit: April 2014)
Hardeberg, J.Y., Brettel, H., Schmitt, F.: Spectral characterisation of electronic cameras. In: Electronic Imaging: Processing, Printing, and Publishing in Color, vol. 3409, pp. 100–109. SPIE Proceedings (1998)
Haneishi, H., Hasegawa, T., Hosoi, A., Yokoyama, Y., Tsumura, N., Miyake, Y.: System design for accurately estimating the spectral reflectance of art paintings. Applied Optics 39(35), 6621–6632 (2000)
Barnard, K., Cardei, V.C., Funt, B.: A comparison of computational color constancy algorithms. I: Methodology and experiments with synthesized data. IEEE Transactions on Image Processing 11(9), 972–984 (2002)
Wang, X., Thomas, J.B., Hardeberg, J.: Discrete wavelet transform based multispectral filter array demosaicking. In: IEEE Colour and Visual Computing Symposium, CVCS (September 2013)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Shrestha, R., Hardeberg, J.Y. (2014). How Are LED Illumination Based Multispectral Imaging Systems Influenced by Different Factors?. In: Elmoataz, A., Lezoray, O., Nouboud, F., Mammass, D. (eds) Image and Signal Processing. ICISP 2014. Lecture Notes in Computer Science, vol 8509. Springer, Cham. https://doi.org/10.1007/978-3-319-07998-1_8
Download citation
DOI: https://doi.org/10.1007/978-3-319-07998-1_8
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07997-4
Online ISBN: 978-3-319-07998-1
eBook Packages: Computer ScienceComputer Science (R0)