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bimagicLab |
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bioimage informatics lab |
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Research The main focus in
our lab is on building automated systems for processing and interpretation of
biological images. To that end, we use both the tools already developed in
signal and image processing and machine learning as well as develop new tools
specifically tailored to the problem at hand. |
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Current research
areas We focus on developing automated systems for
analysis and interpretation of biological images. Our current work focuses on
efficient acquisition of fluorescence microscopy data sets, segmentation of
such data sets as well as classification of protein subcellular location
patterns. Frames are redundant representations which
have become popular in recent years. Work here focuses on characterizing finite-dimensional
frames, searching for useful frame families as well as applying frames to
biomolecular and cellular imaging and biometrics. This area was started by Markus Püschel,
whose goal is to formulate an algebraic framework for signal processing. Our
current work focuses on understanding and formulating such a framework for
filter banks and multiresolution transforms. Correlation, as a pattern recognition tool,
may be applied to texture features that have joint locality in space and
frequency. Wavelets produce these types of discriminatory features, and we
can prune wavelet packets to recover the best subspaces for correlation
filter recognition. |
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Past research areas Multiple descriptions This is a technique where the data is broken
into several streams with some redundancy among the streams. When all the streams
are received, one can guarantee low distortion at the expense of having a
slightly higher bit rate than a system designed purely for compression. On
the other hand, when only some of the streams are received, the quality of
the reconstruction degrades gracefully, which is very unlikely to happen with
a system designed purely for compression. MD filter banks and wavelets One of the first works on multidimensional
filter banks and associated wavelet bases including the first examples of a
regular irreducible two-dimensional wavelet as well as an orthonormal and
symmetric two-dimensional wavelet basis. There is also a brief description on
building local orthogonal bases in multiple dimensions as well as assorted
applications such as HDTV representation and coding, use of three-dimensional
filter banks with the FCO lattice and
deinterlacing by successive approximation. Local orthogonal bases Local cosine bases, or, MDCT, have been
shown to be very useful in audio and image coding. Some video works contain
local cosine bases as well. For that reason, I investigated the local cosine
bases in two dimensions. Moreover, a general framework was put into place
leading to local orthogonal bases usable for audio, image and video coding. Arbitrary tilings One of the main goals of signal analysis in
recent years has been to develop a mixed signal representation in terms of
some elementary blocks well localized in time and frequency, where these
blocks are known as time-frequency atoms. Each one of these blocks would
reside mostly in a well-defined area (usually a rectangle) in the
time-frequency plane. We discuss here several ways of building these
arbitrary tilings, with particular emphasis on those obtainable from local
orthogonal bases. Nonuniform filter banks The most studied case of filter banks is the
one with integer sampling factors. However, if one wants to analyze the
signal into unequal subbands (such as in acoustics), rational sampling
factors have to be allowed. You can find here about two solutions to the open
problem of constructing nonuniform filter banks. The first is general while
the second one is based on local orthogonal bases. As a result of the second
one, we were able to build a critical-band filter bank for use in audio
coding. Quantization analysis This work was motivated by the need to
obtain even more powerful compression schemes than what is currently
available. For subband systems, unsolved problems with large potential
benefits are in the area of joint design of quantization and filtering. The
work here is one of the few on the subject. Texture work We propose a perceptually-based system for
pattern retrieval and matching. We detect basic visual categories that people
use in judgment of similarity, and design a computational model which accepts
patterns as input, and depending on the query, produces a set of choices that
follow human behavior in pattern matching. Graphics work We propose an efficient simplification
method for regular meshes obtained with a binary subdivision scheme. Our mesh
connectivity is constrained with a quadtree data structure. We propose a
quadtree built especially for this class of meshes having a constant-time
traversal property. We introduce a rate-distortion (RD) framework to decimate
the mesh and build a progressive representation for the model. We apply our
technique to a large dataset of terrains and give extensive experimental results. |