Generalization of SPIHT: Set Partition Coding System

This paper constructs Set PArtition Coding System (SPACS) to combine advantages of different types of set partition coding algorithms. General tree (GT) is an important conception introduced in this paper, which can represent tree set and square set simultaneously. With the help of GT, SPIHT is gene...

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Bibliographic Details
Published in:IEEE transactions on image processing 2015-12
Main Authors: Li, Qiufu, Chen, Derong, Jiang, Wei, Liu, Bingtai, Gong, Jiulu
Format: Article
Language:English
Online Access:Get full text
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Summary:This paper constructs Set PArtition Coding System (SPACS) to combine advantages of different types of set partition coding algorithms. General tree (GT) is an important conception introduced in this paper, which can represent tree set and square set simultaneously. With the help of GT, SPIHT is generalized to construct degree-k SPIHT (k-SPIHT) based on analysis of two kinds of set partition operations. Using the same coding mechanism, SPACS(k; p) is constructed, aided with virtual subbands which are generated by recursive division on the LL band. SPACS belongs to tree-set partition coding algorithms if k and p take smaller values. Especially, SPACS(2,1) is the classical SPIHT. SPACS tends toward block-set partition coding algorithm as k; p increase. Location bit, amplitude bit and unnecessary bit are presented, which can be used to analyze the coding efficiency of SPACS. We compress 256 images with 512512 using SPACS. The numerical results show SPACS achieves some improvements in coding efficiency over SPIHT, especially at very low bitrate. On average, to code every image, SPACS(3,1) (at an average of 3.93 bpp) needs 7792 more location bits but saves 10218 unnecessary bits, compared with SPIHT (3.94 bpp).
ISSN:1941-0042