Enhanced Binary MQ Arithmetic Coder with Look-Up Table

Binary MQ arithmetic coding is widely used as a basic entropy coder in multimedia coding system. MQ coder esteems high in compression efficiency to be used in JBIG2 and JPEG2000. The importance of arithmetic coding is increasing after it is adopted as a unique entropy coder in HEVC standard. In the...

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Bibliographic Details
Published in:Information (Basel) Vol. 12; no. 4; p. 143
Main Author: Ko, Hyung-Hwa
Format: Journal Article
Language:English
Published: Basel MDPI AG 01.04.2021
Subjects:
Approximation
Arithmetic coding
Binary codes
binary MQ arithmetic coder
Coding standards
Data compression
Efficiency
Entropy
Image coding
Image compression
JBIG2
JPEG2000
Lookup tables
Measurement
Multimedia
Multiplication
Multiplication & division
Probability
probability estimation lookup table
Propagation
Recursive functions
Software
Video compression
ISSN:2078-2489, 2078-2489
Online Access:Get full text
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Summary:Binary MQ arithmetic coding is widely used as a basic entropy coder in multimedia coding system. MQ coder esteems high in compression efficiency to be used in JBIG2 and JPEG2000. The importance of arithmetic coding is increasing after it is adopted as a unique entropy coder in HEVC standard. In the binary MQ coder, arithmetic approximation without multiplication is used in the process of recursive subdivision of range interval. Because of the MPS/LPS exchange activity that happens in the MQ coder, the output byte tends to increase. This paper proposes an enhanced binary MQ arithmetic coder to make use of look-up table (LUT) for (A × Qe) using quantization skill to improve the coding efficiency. Multi-level quantization using 2-level, 4-level and 8-level look-up tables is proposed in this paper. Experimental results applying to binary documents show about 3% improvement for basic context-free binary arithmetic coding. In the case of JBIG2 bi-level image compression standard, compression efficiency improved about 0.9%. In addition, in the case of lossless JPEG2000 compression, compressed byte decreases 1.5% using 8-level LUT. For the lossy JPEG2000 coding, this figure is a little lower, about 0.3% improvement of PSNR at the same rate.
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ISSN:2078-2489
2078-2489
DOI:10.3390/info12040143