A theory is presented to analyze images of anisotropic fine-scale surfaces. We investigate the estimates of illuminance flow by using structure tensors. For anisotropic surfaces, both the gradient-based and the Hessian-based tensors will yield deviations from the true illumination orientation. Our theory predicts this deviation. To show the use of this theory, an algorithm is derived that uses both tensors simultaneously to compensate for small amounts of anisotropy. Experimental results with rendered surfaces are shown to conform well to our theory.
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