@TechReport{Shekhovtsov-CAK-2010-35,
author = {Shekhovtsov, Alexander and Hlav{\'a}{\v c}, V{\'a}clav},
title = {Joint Image {GMM} and Shading {MAP} Estimation},
institution = {Department of Cybernetics, Faculty of Electrical Engineering
Czech Technical University},
address = {Prague, Czech Republic},
year = {2010},
month = {January},
type = {Research Report},
number = {K333--35/10, CTU--CMP--2010--03},
pages = {15},
figures = {4},
authorship = {},
psurl = {[Shekhovtsov-TR-2010-03.pdf]},
project = {ICT-215078 DIPLECS, 1M0567 CAK},
annote = {We consider a simple statistical model of the image, in
which the image is represented as a sum of two parts: one
part is explained by an i.i.d. color Gaussian mixture and
the other part is a (piecewise-)smoothly varying grayscale
shading function. The smoothness is ensured by a quadratic
(Tikhonov) or total variation regularization. We derive an
EM algorithm to estimate simultaneously the parameters of
the mixture model and the shading. Our algorithms solve for
shading and mean parameters of the mixture model jointly for
both kinds of the regularization.},
keywords = {Total variation, decomposition, shading, retinex},
comment = { },
}