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Comparison of linear spectral reconstruction methods for multispectral imaging

This paper compares the performance of a number of linear methods for reflectance estimation from digital camera responses. Methods based upon smoothness maximisation, linear models of reflectance and least-squares fitting are compared using two simulated 6-channel camera systems. In our experiments, the smoothness methods were generally found to deliver the best performance on test data. Furthermore, they deliver equivalent performance on training data, even compared to those methods that make explicit use of a priori knowledge of the training data.