@Article{Supelec559,
author = {Isidore-Paul Akambita and Michel Barret and Dinh-Tuan Pham},
title = {{On optimal transforms in lossy compression of multicomponent images with JPEG2000}},
journal = {Signal Processing},
year = {2010},
volume = {90},
number = {3},
pages = {759-773},
month = {mars},
url = {http://dx.doi.org/10.1016/j.sigpro.2009.09.011},
doi = {10.1016/j.sigpro.2009.09.011},
abstract = {It is well known in transform coding, that the Karhunen–Loeve
transform (KLT) is optimal only for Gaussian sources. However,
in many applications using JPEG2000 Part 2 codecs, the KLT is
generally considered as the optimal linear transform for reducing
redundancies between components of multicomponent images. In
this paper we present the criterion satisfied by an optimal
transform of a JPEG2000 compatible compression scheme, under
high resolution quantization hypothesis and without the
Gaussianity assumption. We also introduce two variants of the
compression scheme and the associated criteria minimized by
optimal transforms. Then we give two algorithms, derived of the
Independent Component Analysis algorithm ICAinf, that compute
the optimal transform, one under the orthogonality constraint
and the other without no constraint but invertibility. The
computational complexity of the algorithms is evaluated.
Finally, comparisons with the KLT are presented on hyperspectral
and multispectral satellite images with different measures of
distortion, as it is recommended for evaluating the performances
of the codec in applications (like classification and target
detection). For hyperspectral images, we observe a little but
significant gain at medium and high bit-rates of the optimal
transforms compared to the KLT. The actualdrawback of the
optimal transforms is their heavy computational complexity.}
}