Paper Info
Title
Optimized decomposition basis using Lanczos filters for lossless compression of biomedical images
Abstract
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.
Year
DOI
Venue
2010
10.1109/MMSP.2010.5662005
Multimedia Signal Processing
Keywords
Field
DocType
biomedical MRI,data compression,image coding,image denoising,medical image processing,orthogonal codes,wavelet transforms,3D-MRI,Lanczos interpolation filters,Lanczos parameter,biomedical image compression,biorthogonal wavelet,dyadic decomposition,embedded lossy compression,generic packet structure,large scale database,lossless compression,optimized decomposition,wavelet atoms
Computer vision,Lanczos resampling,Pattern recognition,Lossy compression,Computer science,Interpolation,Artificial intelligence,Data compression,Wavelet transform,Lossless compression,Biorthogonal wavelet,Wavelet
Conference
ISBN
Citations 
PageRank 
978-1-4244-8111-8
0
0.34
References 
Authors
11
2
Name
Order
Citations
PageRank
Jonathan Taquet100.34
Claude Labit200.34