Perceptual Zero-Tree Coding with Efficient Optimization for Embedded Platforms
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Abstract
This study proposes a block-edge-based perceptual zero-tree coding (PZTC) method, which is implemented with efficientoptimization 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 wasimplemented as a fixed-point version and optimized on the DSP-based platform based on both the presented platformindependentand platform-dependent optimization technologies. For platform-dependent optimization, this study examinesthe 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. Theperformance, such as compression quality and efficiency, is validated by experimental results.
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How to Cite
Wu, B. F., Huang, H. Y., Wang, J. H., Chen, C. J., & Chen, Y. L. (2013). Perceptual Zero-Tree Coding with Efficient Optimization for Embedded Platforms. Journal of Applied Research and Technology, 11(4). https://doi.org/10.1016/S1665-6423(13)71556-6
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