科研之友
微信
新浪微博
Facebook
分享链接
摘要
A wavelet-based Wiener filter is proposed for signal sparse representation since the classical wavelet transform can not posses good sparse results for real signals. The proposed method can adaptively decrease the magnitude of each wavelet coefficient so that sparsity and compressibility of the wavelet coefficients is improved. This results in improvement of recovered signal quality of the compressed sensing algorithm. Simulation results show that, compared to the original sparse representation based on wavelet transform, the proposed algorithm can significantly improve quality of recovered signals for both signals and images.
- 出版日期2012
- 单位北京交通大学
