Our work in this area includes research into linear fusing of hyperspectral or time-series image sets into one color image that is designed for the human visual system and standard sRGB displays. Also, recent work considers principal component analysis (PCA) for dimensionality reduction where the PCA is done on wavelet coefficients.

Publications:

"Linear Fusion of Image Sets for Display," N. P. Jacobson and M. R. Gupta and J. B. Cole, IEEE Trans. on Geosciences and Remote Sensing , vol. 45, no. 10, 3277-3288, 2007. Code for basis functions, and passive radar videos

"SNR-adaptive Linear Fusion of Hyperspectral Images for Color Display," Nathaniel P. Jacobson and Maya R. Gupta, IEEE Intl. Conf. on Image Processing, 2007.

"Wavelet principal component analysis and its application to hyperspectral imagery," Maya R. Gupta and Nathaniel P. Jacobson, IEEE Intl. Conf. on Image Processing , 2006.

"Design goals and solutions for display of hyperspectral images," Jacobson N.P. and Gupta M.R., IEEE Transactions on Geoscience and Remote Sensing, vol. 43, no. 11, pp. 2684-2692, 2005. AVIRIS image rendering code

"Display of Hyperspectral Imagery by Spectral Weighting Envelopes," Nathaniel P. Jacobson and Maya R. Gupta, Proceedings of the IEEE Intl. Conf. on Image Processing, pp. 622-625, 2005.