Perceptual zero-tree coding with efficient optimization for embedded platforms

Bing-Fei Wu, H. Y. Huang, J. H. Wang, C. J. Chen, Y. L. Chen

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


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 platformindependent 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.

Original languageEnglish
Pages (from-to)487-495
Number of pages9
JournalJournal of Applied Research and Technology
Issue number4
StatePublished - 1 Jan 2013


  • Computational complexity
  • Embedded system
  • Image compression
  • Optimization


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