Variations in illumination on a scene and trichromatic sampling by the eye limit inferences about scene content. The aim of this work was to elucidate these limits in relation to an ideal observer using color signals alone. Simulations were based on 50 hyperspectral images of natural scenes and daylight illuminants with correlated color temperatures $4000\mathrm{K}$ , $6500\mathrm{K}$ , and $\mathrm{25,000}\mathrm{K}$ . Estimates were made of the (Shannon) information available from each scene, the redundancies in receptoral and postreceptoral coding, and the information retrieved by an observer identifying corresponding points across image pairs. For the largest illuminant difference, between $\mathrm{25,000}\mathrm{K}$ and $4000\mathrm{K}$ , a postreceptoral transformation providing minimum redundancy yielded an efficiency of about 80% in the information retrieved. This increased to about 89% when the transformation was optimized directly for information retrieved, corresponding to an equivalent Gaussian noise amplitude of 3.0% or to a mean of $3.6\times {10}^4$ distinct identifiable points per scene. Using color signals to retrieve information from natural scenes can approach ideal observer efficiency levels.

© 2009 Optical Society of America

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