Home

About

Advanced Search

Browse by Discipline

Scientific Societies

E-print Alerts

Add E-prints

E-print Network
FAQHELPSITE MAPCONTACT US


  Advanced Search  

 
A COMPRESSED SENSING APPROACH FOR BIOLOGICAL MICROSCOPIC IMAGE Marcio M. Marim1,2
 

Summary: A COMPRESSED SENSING APPROACH FOR BIOLOGICAL MICROSCOPIC IMAGE
PROCESSING
Marcio M. Marim1,2
, Elsa D. Angelini2
, J.-C. Olivo-Marin1
1
Institut Pasteur, Unit´e d'Analyse d'Images Quantitative CNRS URA 2582, F-75015 Paris
2
Institut TELECOM, TELECOM ParisTech CNRS LTCI, F-75013 Paris
ABSTRACT
In fluorescence microscopy the noise level and the photobleaching
are cross-dependent problems since reducing exposure time to re-
duce photobleaching degrades image quality while increasing noise
level. These two problems cannot be solved independently as a post-
processing task, hence the most important contribution in this work
is to a-priori denoise and reduce photobleaching simultaneously by
using the Compressed Sensing framework (CS). In this paper, we
propose a CS-based denoising framework, based on statistical prop-
erties of the CS optimality, noise reconstruction characteristics and
signal modeling applied to microscopy images with low signal-to-

  

Source: Angelini, Elsa -Département Traitement du Signal et des Images, Telecom ParisTech

 

Collections: Engineering; Biology and Medicine