Introduction - If you have any usage issues, please Google them yourself
Compressive sensing, a novel signal acquisition method, is a joint sensing-compression process which requires a small number of measurements to reconstruct signal. Measurement matrix, a very important part in compressive sensing, directly affects the adaptive sparsity, the required number of measurements and the reconstruct performance of the signal. In order to decrease the mutual coherence between the measurement matrix and sparse transformed
matrix and improve the quality of reconstruction, this paper addresses the joint optimization between measurement matrix and sparse dictionary based on the KSVD-ETF. While optimizing the measurement matrix by ETF, we use the
KSVD method to update the dictionary. The PSNR of the reconstructed signal is improved with the optimized measurement matrix the experimental results, indicating that this method of optimizing the measurement matrix has
certain advantages in the effect of reconstruction.