Perceptual Zero-Tree Coding with Efficient Optimization for Embedded Platforms

 

B. F. Wu¹, H. Y. Huang¹, J. H. Wang³, C. J. Chen², Y. L. Chen*³

 

¹ Institute of Electrical and Control Engineering National Chiao Tung University Hsinchu, Taiwan.

² CSSP Inc. Hsinchu, Taiwan.

³ Dept. of Computer Science & Information Engineering National Taipei University of Technology Taipei, Taiwan. *ylchen@ntut.edu.tw.

 

ABSTRACT

This study proposes a block-edge-based perceptual zero-tree coding (PZTC) method, which is implemented with efficient optimization on the embedded platform. PZTC combines two novel compression concepts for coding efficiency and quality: block-edge detection (BED) and the low-complexity and low-memory entropy coder (LLEC). The proposed PZTC was implemented as a fixed-point version and optimized on the DSP-based platform based on both the presented platform-independent and platform-dependent optimization technologies. For platform-dependent optimization, this study examines the fixed-point PZTC and analyzes the complexity to optimize PZTC toward achieving an optimal coding efficiency. Furthermore, hardware-based platform-dependent optimizations are presented to reduce the memory size. The performance, such as compression quality and efficiency, is validated by experimental results.

Keywords: Computational complexity, image compression, embedded system, optimization.

 

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Acknowledgements

This work is supported by the National Science Council of the Republic of China under Contract No. NSC-1002221-E-027-033, NSC-101-2219-E-027-006.

 

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