文件名称:AO-2013
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Real-time highlight removal using intensity ratio
In this paper, we propose an efficient method to separate the diffuse and specular reflection components
from a single image. The method is built on the observation that, for diffuse pixels, the intensity ratios
between the maximum values and range values (maximums minus minimums) are independent
of surface geometry. The specular fractions of the image pixels can then be computed by using the
intensity ratio. For textured surfaces, image pixels are classified into clusters by constructing a pseudochromaticity
space, and the intensity ratio of each cluster is robustly estimated. Unlike existing
techniques, the proposed method works in a pixel-wise manner, without specular pixel identification
and any local interaction.
In this paper, we propose an efficient method to separate the diffuse and specular reflection components
from a single image. The method is built on the observation that, for diffuse pixels, the intensity ratios
between the maximum values and range values (maximums minus minimums) are independent
of surface geometry. The specular fractions of the image pixels can then be computed by using the
intensity ratio. For textured surfaces, image pixels are classified into clusters by constructing a pseudochromaticity
space, and the intensity ratio of each cluster is robustly estimated. Unlike existing
techniques, the proposed method works in a pixel-wise manner, without specular pixel identification
and any local interaction.
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