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

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.