Detection of diffuse and specular interface reflections and inter-reflections by color image segmentation

We present a computational model and algorithm for detecting diffuse and specular interface reflections and some inter-reflections. Our color reflection model is based on the dichromatic model for dielectric materials and on a color space, called S space, formed with three orthogonal basis functions. We transform color pixels measured in RGB into the S space and analyze color variations on objects in terms of brightness, hue and saturation which are defined in the S space. When transforming the original RGB data into the S space, we discount the scene illumination color that is estimated using a white reference plate as an active probe. As a result, the color image appears as if the scene illumination is white. Under the whitened illumination, the interface reflection clusters in the S space are all aligned with the brightness direction. The brightness, hue and saturation values exhibit a more direct correspondence to body colors and to diffuse and specular interface reflections, shading, shadows and inter-reflections than the RGB coordinates. We exploit these relationships to segment the color image, and to separate specular and diffuse interface reflections and some inter-reflections from body reflections. The proposed algorithm is effications for uniformly colored dielectric surfaces under singly colored scene illumination. Experimental results conform to our model and algorithm within the liminations discussed.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/41303/1/11263_2004_Article_BF00128233.pd

Photoreceptor Sensitivity Changes Explain Color Appearance Shifts Induced by Large Uniform Backgrounds In Dichoptic Matching

this paper we ask two questions. Do photoreceptor sensitivity (gain) changes explain the effects of uniform backgrounds on color appearance? If so, how do apparent receptor sensitivities depend on background light? At the turn of the century von Kries hypothesized that the background exerts its influence on appearance by altering photoreceptor sensitivity (von Kries 1905). Color appearance studies since von Kries have not decisively tested his hypothesis. In the earliest studies, several authors rejected receptor sensitivity changes (Burnham, Evans et al. 1952; MacAdam 1956; Wassef 1959). We will argue in the Discussion that their conclusions were undermined by not knowing the human cone spectral sensitivities and by unstable adaptation. In spite of these findings, many authors have assumed that receptor sensitivity changes affect the appearance of targets viewed on uniform backgrounds (Jameson and Hurvich 1972; Walraven 1976; Shevell 1978; Werner and Walraven 1982). Brainard and Wandell (Brainard and Wandell 1992) found evidence for receptor sensitivity control in more complex simulated illumination conditions. These conflicting findings led us to re

Applications of a spatial extension to CIELAB

We describe computational experiments to predict the perceived quality of multi-level halftone images. Our computations were based on a spatial color difference metric, S-CIELAB, that is an extension of CIELAB, a widely used industry standard. CIELAB predicts the discriminability of large uniform color patches. S-CIELAB includes a pre-processing stage that accounts for certain aspects of the spatial sensitivity to different colors. From simulations applied to multi-level halftone images, we found that (a) for grayscale images, L -spacing of the halftone levels results in better halftone quality than linear-spacing of the levels; (b) for color images, increasing the number of halftone levels for magenta ink results in the most significant improvement in halftone quality. Increasing the number of halftone levels of the yellow ink resulted in the least improvement. 1. Introduction For many image systems engineering applications it is useful to predict the visual effect of changes in ..