Lambert's model for diiuse reeection is extensively used in computational vision. For several real-world objects, the Lambertian model can prove to be a very inaccurate approximation to the diiuse component. While the brightness of a Lambertian surface is independent of viewing direction, the brightness of a rough diiuse surface increases as the viewer approaches the source direction. A compreh...

For improved multispectral classification and retrieval of Lambertian reflectances from patches of arbitrary surface orientation, we investigate the consequences of a dichromatic illumination model accounting for direct sunlight and diffuse skylight. This illumination model leads to the concept of spectral classes as two dimensional planes in the feature space. This paper addresses three questi...

Traditional shape from shading methods are based on the Lambertian surface model. Real images often contain specularities which violate this assumption and lead to undesired results. In [1] a method for color subspace based specularity removal has been proposed. This method only works with a good estimate of the source color given as a vector in RGB space. In this project we present two novel m...

We present an algorithm for separating the local gradient information and Lambertian color by using 4-source color photometric stereo in the presence of highlights and shadows. We assume that the surface reflectance can be approximated by the sum of a Lambertian and a specular component. The conventional photometric method is generalized for color images. Shadows and highlights in the input ima...

A maximum likelihood method for estimating remote surface orientation from multi-static acoustic, optical, radar, or laser images is presented. It is assumed that the images are corrupted by signal-dependent noise, known as speckle, arising from complex Gaussian field fluctuations, and that the surface properties are effectively Lambertian. Surface orientation estimates for a single sample are ...

Heuristic optimisers which search for an optimal configuration of variables relative to an objective function often get stuck in local optima where the algorithm is unable to find further improvement. The standard approach to circumvent this problem involves periodically restarting the algorithm from random initial configurations when no further improvement can be found. We propose a method of ...

We present a new method for the detection and estimation of multiple directional illuminants, using only one single image of an object of arbitrary known geometry. The surface is not assumed to be pure Lambertian, instead, it can have both Lambertian and specular properties. We propose a novel methodology that integrates information from shadows, shading and specularities in the presence of str...

— This paper considers optimum ordering policies minimizing the expected cost per unit time in the steady-state. It is assumed that a lead time for the spare is constant and order costs depend on time. It is shown in theorem that there exists afinite and unique optimum ordering policy under certain conditions.