Result: Optimized decomposition basis using Lanczos filters for lossless compression of biomedical images
Title:
Optimized decomposition basis using Lanczos filters for lossless compression of biomedical images
Authors:
Contributors:
Digital image processing, modeling and communication (TEMICS), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Centre Inria de l'Université de Rennes, Institut National de Recherche en Informatique et en Automatique (Inria), This research was supported by the co-funded Brittany Council & INRIA doctoral research grant contract n°4591
Source:
2010 IEEE International Workshop on Multimedia Signal Processing (MMSP 2010), Oct 2010, SAINT MALO, France
Publisher Information:
CCSD, 2010.
Publication Year:
2010
Collection:
collection:EC-PARIS
collection:UNIV-RENNES1
collection:CNRS
collection:INRIA
collection:INSA-RENNES
collection:INRIA-RENNES
collection:IRISA
collection:IRISA_SET
collection:INRIA_TEST
collection:TESTALAIN1
collection:IRISA-D5
collection:INRIA2
collection:UR1-HAL
collection:UR1-MATH-STIC
collection:UR1-UFR-ISTIC
collection:TEST-UNIV-RENNES
collection:TEST-UR-CSS
collection:UNIV-RENNES
collection:INRIA-RENGRE
collection:INRIA-300009
collection:INSA-GROUPE
collection:UR1-MATH-NUM
collection:UNIV-RENNES1
collection:CNRS
collection:INRIA
collection:INSA-RENNES
collection:INRIA-RENNES
collection:IRISA
collection:IRISA_SET
collection:INRIA_TEST
collection:TESTALAIN1
collection:IRISA-D5
collection:INRIA2
collection:UR1-HAL
collection:UR1-MATH-STIC
collection:UR1-UFR-ISTIC
collection:TEST-UNIV-RENNES
collection:TEST-UR-CSS
collection:UNIV-RENNES
collection:INRIA-RENGRE
collection:INRIA-300009
collection:INSA-GROUPE
collection:UR1-MATH-NUM
Subject Terms:
ACM: E.: Data, E.4: CODING AND INFORMATION THEORY, E.4.0: Data compaction and compression, [INFO.INFO-IM]Computer Science [cs], Medical Imaging, [INFO.INFO-IT]Computer Science [cs], Information Theory [cs.IT], [MATH.MATH-IT]Mathematics [math], Information Theory [math.IT], [INFO.INFO-TS]Computer Science [cs], Signal and Image Processing, [SPI.SIGNAL]Engineering Sciences [physics], Signal and Image processing
Subject Geographic:
Original Identifier:
HAL:
Document Type:
Conference
conferenceObject<br />Conference papers
Language:
English
Availability:
Accession Number:
edshal.inria.00538797v1
Database:
HAL
Further Information
This paper proposes to introduce Lanczos interpolation filters as wavelet atoms in an optimized decomposition for embedded lossy to lossless compression of biomedical images. The decomposition and the Lanczos parameter are jointly optimized in a generic packet structure in order to take into account the various contents of biomedical imaging modalities. Lossless experimental results are given on a large scale database. They show that in comparison with a well known basis using 5/3 biorthogonal wavelets and a dyadic decomposition, the proposed approach allows to improve the compression by more than 10\% on less noisy images and up to 30% on 3D-MRI while providing similar results on noisy datasets.