DocumentCode :
442787
Title :
Interleaved S+P pyramidal decomposition with refined prediction model
Author :
Babel, Marie ; Déforges, Olivier ; Ronsin, Joseph
Author_Institution :
IETR UMR CNRS, INSA, Rennes, France
Volume :
2
fYear :
2005
fDate :
11-14 Sept. 2005
Abstract :
Scalability and others functionalities such as the region of interest encoding become essential properties of an efficient image coding scheme. Within the framework of lossless compression techniques, S+P and CALIC represent the state-of-the-art. The proposed interleaved S+P algorithm outperforms these method while providing the desired properties. Based on the LAR (locally adaptive resolution) method, an original pyramidal decomposition combined with a DPCM scheme is elaborated. This solution uses the S-transform in such a manner that a refined prediction context is available for each estimation steps. The image coding is done in two main steps, so that the first one supplies a LAR low-resolution image of good visual quality, and the second one allows a lossless reconstruction. The method exploits an implicit context modelling, intrinsic property of our content-based quad-tree like representation.
Keywords :
data compression; image coding; image reconstruction; image representation; image resolution; interleaved codes; transforms; content-based quad-tree like representation; image coding scheme; image reconstruction; interleaved S+P pyramidal decomposition; locally adaptive resolution; lossless compression techniques; refined prediction model; region of interest encoding; Codecs; Context modeling; IP networks; Image coding; Image reconstruction; Image resolution; Predictive models; Remote sensing; Scalability; Spatial resolution;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 2005. ICIP 2005. IEEE International Conference on
Print_ISBN :
0-7803-9134-9
Type :
conf
DOI :
10.1109/ICIP.2005.1530164
Filename :
1530164
Link To Document :
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