@InProceedings{Supelec462,
author = {Isidore-Paul Akambita and Michel Barret and Florio Dalla Vedova and Jean-Louis Gutzwiller},
title = {{Onboard Hyperspectral images compression with exogenous quasi optimal coding transforms}},
year = {2008},
booktitle = {{On-Board Payload Data Compression Workshop, ESA OBPDC 2008}},
pages = {8 pages},
organization = {ESA/ESTEC},
url = {http://hal-supelec.archives-ouvertes.fr/hal-00340194/fr/},
abstract = {In previous works, we defined the Optimal Transform Code (OTC)
assuming high rate coding and using the asymptotical Bennett
approximation of the rate. We showed that the OTC gives the
optimal linear transform of a multicomponent image compression
scheme which consists in applying a linear transform that
adapts
to the encoded image for reducing the spectral redundancy and a
fixed 2-D Discrete Wavelet Transform (DWT) per component for
reducing the spatial redundancy. The performances in terms of
rate vs PSNR (Peak of Signal to Noise Ratio) are very
attractive
when evaluated with the Verification Model version 9 of the
JPEG2000 committee which is a JPEG2000 codec (coding-decoding).
The transform in OTC performs better than the Karhunen Loeve
Transform (KLT). The drawback of the OTC is its high computing
complexity, since the optimal linear transform must be computed
for each encoded image. In order to implement the OTC in an on-
board satellite real-time codec system, we propose to pass
round
the problem of computing complexity by learning only one fixed
transform with the OTC algorithms from a set of images instead
of computing a new transform for each image. We call the fixed
transform computed in this way an exogenous quasi-optimal
linear
transform. In this paper, we focus the study on hyperspectral
images. Our set of images is constituted of ten Hyperion3
hyperspectral images. We have separated the VNIR and the SWIR
bands (since they are obtained with two different sensors on-
board) and we just focus on the VNIR spectral bands. }
}