TY - JOUR
T1 - Lossy-to-lossless 3D image coding through prior coefficient lookup tables
AU - Aulí-Llinàs, Francesc
AU - Marcellin, Michael W.
AU - Serra-Sagristà, Joan
AU - Bartrina-Rapesta, Joan
N1 - Funding Information:
The authors thank the anonymous reviewers and the associate editor for their comments and suggestions, which helped to improve the quality of the manuscript. This work has been partially supported by the European Union , by the Spanish Government (MINECO) , by FEDER , and by the Catalan Government , under Grants RYC-2010-05671, FP7-PEOPLE-2009-IIF-250420, TIN2009-14426-C02-01, TIN2012-38102-C03-03, and 2009-SGR-1224 .
PY - 2013/8/1
Y1 - 2013/8/1
N2 - This paper describes a low-complexity, high-efficiency, lossy-to-lossless 3D image coding system. The proposed system is based on a novel probability model for the symbols that are emitted by bitplane coding engines. This probability model uses partially reconstructed coefficients from previous components together with a mathematical framework that captures the statistical behavior of the image. An important aspect of this mathematical framework is its generality, which makes the proposed scheme suitable for different types of 3D images. The main advantages of the proposed scheme are competitive coding performance, low computational load, very low memory requirements, straightforward implementation, and simple adaptation to most sensors.
AB - This paper describes a low-complexity, high-efficiency, lossy-to-lossless 3D image coding system. The proposed system is based on a novel probability model for the symbols that are emitted by bitplane coding engines. This probability model uses partially reconstructed coefficients from previous components together with a mathematical framework that captures the statistical behavior of the image. An important aspect of this mathematical framework is its generality, which makes the proposed scheme suitable for different types of 3D images. The main advantages of the proposed scheme are competitive coding performance, low computational load, very low memory requirements, straightforward implementation, and simple adaptation to most sensors.
KW - 3D image coding
KW - Bitplane image coding
KW - Entropy coding
KW - JPEG2000
UR - http://www.scopus.com/inward/record.url?scp=84876942280&partnerID=8YFLogxK
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U2 - 10.1016/j.ins.2013.03.027
DO - 10.1016/j.ins.2013.03.027
M3 - Article
AN - SCOPUS:84876942280
SN - 0020-0255
VL - 239
SP - 266
EP - 282
JO - Information Sciences
JF - Information Sciences
ER -