A New Wavelet-Based Compressive Sensing for Image Compression
Compressive sensing (CS) technique can capture and represent compressible signal at a rate below the Nyquist rate of sampling. In this paper, the compressive sensing principles are studied and a new wavelet-based coding method is proposed. Two-dimentional discrete wavelet transform (DWT) is applied for sparse representation. Then the wavelet coefficients are divided into four blocks and are compressed by four different sensing matrixes respectively. The recovery quality depends on the number of received CS measurements. Experimental results show that the proposed coding method achieving higher performance compared with the conventional wavelet-based compressive sensing coding system. With 50% coefficients retained, the image can still be recovered with considerably objective and subjective quality.
S.Z. Cai and Q.F. Zhang
W. Jiang and J. J. Yang, "A New Wavelet-Based Compressive Sensing for Image Compression", Advanced Materials Research, Vols. 756-759, pp. 1684-1690, 2013