Parametric investigation of Multispectral imaging

摘要

Multi-spectral imaging systems can be used to recover estimates of the spectral reflectance properties of surfaces in an image. This process can be aided by utilising a priori knowledge of the reflectance spectra derived from linear models of surface reflectance. We use this recovery method in a simulated camera system, and investigate the effect of varying sensor characteristics and illuminants on the accuracy of the system. We also investigate the effect of quantisation noise and random sensor noise on the process. Unlike other recovery methods, increasing the number of sensors in the system-and hence the number of basis functions used in the linear model-does not necessarily improve performance. We find that increasing the amount of noise increases reconstruction error and it does so to a greater extent for large sensor numbers and large sensor band-widths. The robustness of the process to noise is improved by using illuminants that have approximately equal power across all visible wavelengths of light.