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Compressive sampling based image coding using wavelet domain signal characteristics and human visual property

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2 Author(s)
Day-Fann Shen ; Electrical Engineering, National Yunlin University of Science and Technology, Taiwan ; Wang Yung-Shiang

The contribution of this paper to compressive sampling (CS) based image coding is two-fold. Firstly, we propose more accurate CS performance metrics: 1. Adopt bit-rate to replace common but inaccurate measurement rate in R-D performance. 2. Algorithm complexity is measured by the elapsed execution time and their ratios. Secondly, we improve the R-D performance by exploiting wavelet domain signal characteristics and human visual property. Experimental results show that the proposed schemes can improve PSNR by 3.5 dB (0.75 bpp) to 6 dB (1.5 bpp) at cost of increased codec complexity of 106.3% and 109.2% respectively.

Published in:

Multimedia Technology (ICMT), 2011 International Conference on

Date of Conference:

26-28 July 2011