Improving the Signal-to-Noise Ratio of Superresolution Imaging Based on Single-Pixel Camera

Ziran Wei, Jianlin Zhang, Zhiyong Xu, Yong Liu, Yongmei Huang, Xiangsuo Fan
2019 IEEE Photonics Journal  
IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. See for more information. Abstract: Based on the theories of single-pixel camera and compressed sensing image reconstruction, the sparse basis, the projection method of measurement matrix, and the signal reconstruction algorithm are optimized. First, for
more » ... the sparse representation of image, the restraint matrix is designed combining the characteristics of wavelet sparse coefficients to enhance the sparse representation ability of the discrete wavelet base, which improves the quality of image reconstruction and imaging by single-pixel camera. Then, in the singlepixel camera system, the projection method is improved according to the characteristics of the digital mirror device micromirror, and a new bilateral projection method based on the block diagonal measurement matrix is proposed to realize the superresolution imaging of the outdoor scene, reducing the number of measurement and improving the imaging quality. Finally, for the algorithm of image reconstruction, combining the characteristics of convex optimization and nonconvex optimization algorithms, a new algorithm from convex optimization approximately to nonconvex optimization algorithm is proposed, and compared with the traditional image reconstruction algorithm, such as greedy pursuit algorithm, minimum norm algorithm, and image interpolation, the peak signal-to-noise ratio and imaging quality of reconstructed images are effectively improved. The feasibility of the proposed methods is demonstrated by simulation experiments and imaging experiments of single-pixel camera.
doi:10.1109/jphot.2019.2891061 fatcat:7qoz5wgcxbf6jawrzx7qdlupoy