Fast compressed sensing spectral measurement with adaptive gradient multiscale resolution

We propose a fast, adaptive multiscale resolution spectral measurement method based on compressed sensing. The method can apply variable measurement resolution over the entire spectral range to reduce the measurement time by over 75% compared to a global high-resolution measurement. Mimicking the characteristics of the human retina system, the resolution distribution follows the principle of gradually decreasing. The system allows the spectral peaks of interest to be captured dynamically or to b...     

压缩感知光谱测量局部哈达玛矩阵的构造与性能

针对压缩感知光谱测量中随机矩阵作为测量矩阵无法获得高质量重建精度问题,提出了一种测量矩阵构造的新方法。介绍了局部哈达玛矩阵的构造方法,以随机测量矩阵为比较对象,通过仿真实验对局部哈达玛矩阵在压缩感知光谱测量中的性能进行分析。实验结果表明,相对于随机矩阵,新型局部哈达玛矩阵下的重建光谱与原始光谱重合度大大提高,在100%采样率时,定量指标MSE为3.2,实现了光谱的精确重建,25%采样率的MSE指标水平已经与随机矩阵100%采样率时相当,局部哈达玛矩阵可以有效的改善光谱重建的精度;光谱重建时间大约缩短到1/3,系统具有更好的信噪比特性。     

Compressive imaging based on multi-scale modulation and reconstruction in spatial frequency domain

Imaging quality is a critical component of compressive imaging in real applications. In this study, we propose a compressive imaging method based on multi-scale modulation and reconstruction in the spatial frequency domain. Theoretical analysis and simulation show the relation between the measurement matrix resolution and compressive sensing(CS)imaging quality. The matrix design is improved to provide multi-scale modulations, followed by individual reconstruction of images of different spatial frequencies. Compared with traditional single-scale CS imaging, the multi-scale method provides high quality imaging in both high and low frequencies, and effectively decreases the overall reconstruction error.Experimental results confirm the feasibility of this technique, especially at low sampling rate. The method may thus be helpful in promoting the implementation of compressive imaging in real applications.