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Practical Implementation of LMMSE Demosaicing Using Luminance and

Summary: Practical Implementation of LMMSE
Demosaicing Using Luminance and
Chrominance Spaces.
Brice Chaix de Lavar`ene ,1
, David Alleysson 2
, Jeanny H´erault 1
Most digital color cameras sample only one color at each spatial location, using a sin-
gle sensor coupled with a color filter array (CFA). An interpolation step called demo-
saicing (or demosaicking) is required for rendering a color image from the acquired
CFA image. Already proposed Linear Minimum Mean Square Error (LMMSE) de-
mosaicing provides a good tradeoff between quality and computational cost for
embedded systems. In this paper we propose a modification of the stacked notation
of superpixels, which allows an effective computing of the LMMSE solution from an
image database. Moreover, this formalism is used to decompose the CFA sampling
into a sum of a luminance estimator and a chrominance projector. This decom-
position allows interpreting estimated filters in term of their spatial and chromatic
properties and results in a solution with lower computational complexity than other
LMMSE approaches for the same quality.
Key words: demosaicing, demosaicking, interpolation, color, luminance,


Source: Alleysson, David - Laboratoire de Psychologie et NeuroCognition, Université Pierre Mendes France


Collections: Biology and Medicine