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Abstract:
We present a unified framework for separating specular and diffuse
reflection components in images and videos of textured scenes. This
can be used for specularity removal and for independently processing,
filtering, and recombining the two components. Beginning with a
partial separation provided by an illumination-dependent color space,
the challenge is to complete the separation using spatio-temporal
information. This is accomplished by evolving a partial differential
equation (PDE) that iteratively erodes the specular component at each
pixel. A family of PDEs appropriate for differing image sources (still
images vs. videos), differing prior information (e.g., highly
vs. lightly textured scenes), or differing prior computations (e.g.,
optical flow) is introduced. In contrast to many other methods,
explicit segmentation and/or manual intervention are not required. We
present results on high-quality images and video acquired in the
laboratory in addition to images taken from the Internet. Results on
the latter demonstrate robustness to low dynamic range, JPEG
artifacts, and lack of knowledge of illuminant color. Empirical
comparison to physical removal of specularities using polarization is
provided. Finally, an application termed dichromatic dditing is
presented in which the diffuse and the specular components are
processed independently to produce a variety of visual effects.
For more information, see Satya Mallick's
dichromatic editing page.
References:
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Satya P. Mallick, Todd Zickler, David J. Kriegman, and Peter N. Belhumeur,
"Specularity Removal in Images and Videos: A PDE Approach."
Proc. European Conf. Computer Vision, May 2006.
[PDF]
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