Title :
High-order entropy coding for images
Author_Institution :
Bellcore, Red Bank, NJ, USA
fDate :
3/1/1992 12:00:00 AM
Abstract :
A preliminary study shows the effectiveness of high-order entropy coding for 2-D data. The incremental conditioning tree extension method is the key element for reducing the complexity of high-order statistical coding. The determination of the conditioning state in the nonfull tree for an underlying sample is, in functionality, similar to the extraction of a codeword from a variable length coded bit string. Therefore, the hardware structure used for decoding variable length codes can be applied to determine the conditioning state based on data in the causal region
Keywords :
encoding; entropy; picture processing; trees (mathematics); 2D data; conditioning state; high-order entropy coding; image coding; incremental conditioning tree extension method; nonfull tree; Arithmetic; Binary trees; Bit rate; Conferences; Entropy coding; Equations; Higher order statistics; Probability; Signal processing; Source coding;
Journal_Title :
Circuits and Systems for Video Technology, IEEE Transactions on
