The Optimization Design of Measurement Matrix Based on KSVD-ETF
Abstract: 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 from the experimental results, indicating that this method of optimizing the measurement matrix has certain advantages in the effect of reconstruction.
文章引用: 赵毅智 , 汪立新 , 钱 建 (2014) 一种基于KSVD-ETF的测量矩阵优化方法。 图像与信号处理， 3， 15-18. doi: 10.12677/JISP.2014.31003
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