Perceptual Zero-Tree Coding with Efficient Optimization for Embedded Platforms

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.