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European
project: Implementation of a novel on-board hyperspectral data
compression tool In
2007, the European Space Agency (ESA)
granted 150,000 € for
supporting a 1-year feasibility study on the
application of my Ph.D. thesis to the onboard compression of satellite
images. This achievement was the result of a 6-month personal
initiative to bring together industrial and academic
partners around the applications of my Ph.D. thesis. The project was
carried out in the context of an Innovation Triangle Initiative (ITI),
supported by ESA with LuxSpace, OHB System AG and
Supélec
as partners. The main goal of the project was to develop and
demonstrate the feasibility and use (in a laboratory environment) of a
demonstrator for an on-board satellite image compression system based
on the concept of "Optimal Transform Codes" (OTC)
developed
during my Ph.D. thesis.
Independent component analysis (ICA) and transform coding for image/video compression From
2002 to 2005 I worked as a Research Assistant in the "Information,
Multimodality & Signal" (IMS) research group at Supélec
(Metz, France).
I was interested in independent
component
analysis (ICA) and transform coding for signal (image/video/speech)
compression. In
this position I first proposed a new point of view in transform coding:
the problem of finding the optimal 1-D linear block transform may be
viewed as a modified ICA problem. This result applies without the
presumption of Gaussianity. By adopting this new viewpoint, I then
derived two new ICA-based algorithms, called
GCGsup and
ICAorth, for computing the optimal 1-D linear transform and the optimal
1-D orthogonal
transform, respectively. Experimental results showed that the new
transforms can achieve better visual image quality than the classical
discrete cosine transform (DCT) used in JPEG and MPEG. The new
transforms proved also efficient for the compression of multicomponent
images such as multispectral and hyperspectral satellite images.
Performance comparisons with the classical Karhunen-Loève
transform (KLT) showed that the transforms returned by GCGsup and
ICAorth can achieve better spectral redundancy reduction.
Emergence of Simple-Cell Receptive Field Properties by Learning Optimal Variable-Rate Transform Codes for Natural Images The
receptive
fields of simple cells in mammalian primary visual cortex can be
characterized as being spatially localized, oriented and bandpass,
comparable to the basis functions of wavelet transforms. A fundamental
problem in vision research is to determine why the receptive fields and
response properties of visual neurons are as they are. One approach to
understanding such response properties has been to consider their
relationship to the statistical structure of natural images in terms of
efficient coding. Models for learning efficient codes for natural
images, such as sparse coding or ICA, predict the localized, oriented,
and bandpass characteristics of simple cells. In this work, I propose
a new approach to understanding the response properties of simple
cells, which has its roots in the framework of variable-rate transform
coding. Recently, we proposed a new viewpoint in variable-rate
transform coding. Under the high resolution hypothesis, we showed that
the optimal variable-rate transform code for a signal to be encoded is
the solution of a modified independent component analysis (ICA)
problem. This result applies without the presumption of Gaussianity or
orthogonality. By adopting this new viewpoint, we derived a new
algorithm, called GCGsup, for learning optimal variable-rate transform
codes from a set of signals (e.g., images and sounds) to be encoded. In
this work, we show that optimal variable-rate transform codes for
natural images exhibit a complete family of localized, oriented,
bandpass receptive fields, similar to those found in the primary visual
cortex.
Acoustic mine imaging and sonar From
July
2000 to November 2001 I worked as a R&D Sonar
Engineer in the General
Sonar Studies Group of Thales
Underwater Systems Pty Ltd, Sydney, Australia.
I worked on a 3-D acoustic mine imaging project, the purpose
of
which was to
build an acoustical system capable of overcoming the limits of an
optical camera operating in turbid water. In the context of this
project,
I developed a computer model for the signal processing
chain of the acoustical camera. My
research work
enabled the definition of an optimal array of sensor, which was
essential for obtaining the best image quality.
Automated breast cancer diagnosis From
March
2000 to November 2001 I worked in the Laboratory
of Experimental Oncology of the French Research
Center for Medical Research, Marseille, France as a M.S.
trainee.
I worked at
clinical site on an interdisciplinary team of image processing
researchers, biologists, and medical practitioners to investigate new
methods for automated breast cancer diagnosis. In this position I first
designed and implemented an algorithm for the segmentation of
histological structures in microscopic images using mathematical
morphology operations. Then I proposed a supervised learning technique
for predicting the histologic grade --- in the Scarff-Bloom-Richardson
system --- of a patient's cancerous breast tumor. A good
match
between the grades returned by my predictor and those obtained from
visual inspection by a medical practitioner was observed.
Management of Quality of Service (QoS) in digital T.V. operations covered by the MPEG-2 standard From
July 1999 to October 1999 I worked in the Design and Test of Equipment
Laboratory of the French
Research Center in Broadcasting and Radiocommunications (TDF)
as an Engineer trainee. I
worked on a project related to the management of Quality of
Service
(QoS) in digital T.V. operations (satellite,
cable and terrestrial networks) covered by the MPEG-2 standard. In the
context of this project, I
designed and built an experimental set-up for assessing the performance
of a video quality evaluation system.
Simulation of a fluid flow During
summer 1996 I
worked in the R&D
department of Z.F.,
Saarbrücken, Germany as a Summer Intern. I performed some
simulations (using Matlab and AutoCAD) for the optimization of the
electro-hydraulic brain of an automatic gearbox.
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Last updated: December
2010
Michel
Narozny - Copyright 2006-2010 |