Perceptual Zero-Tree Coding with Efficient Optimization for Embedded Platforms
| Autor: | Yen-Lin Chen, C.J. Chen, Bing-Fei Wu, Jenq-Haur Wang, Huan-Shun Huang |
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| Rok vydání: | 2013 |
| Předmět: |
Computational complexity theory
Computer science business.industry Real-time computing General Engineering image compression Tree coding Computational complexity embedded system Computer engineering Algorithmic efficiency Entropy (information theory) business optimization Digital signal processing Image compression |
| Zdroj: | Journal of Applied Research and Technology. 11:487-495 |
| ISSN: | 1665-6423 |
| DOI: | 10.1016/s1665-6423(13)71556-6 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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