No abstract

Due to ill-posed of the image reconstruction in Electromagnetic tomography (EMT), the condition number of the sensitivity matrix is high and the reconstructed results are sensitive to the measurement errors. In this paper, two weighting matrices are proposed to improve the condition number and two modified Landweber methods are derived. Numerical simulations demonstrate the feasibility of the modified methods.

Coded aperture compressive temporal imaging (CACTI) is the mapping of multiple frames using different encoding patterns into a single measurement and then using an algorithm to reconstruct the required high-dimensional signals, thus enabling high-speed photography on low-speed cameras. An encoding pattern and a reconstruction algorithm both play a critical role for CACTI. To improve the quality of the reconstruction, in terms of encoding, we took advantage of the reflective properties of the digital micromirror device and used a complementary dual-mask pattern to obtain more projection information. In terms of decoding, we developed what we believe, to the best of our knowledge, is a new model combining the weighted Landweber regularization with the relaxation strategy and a deep denoiser. The experimental results show the superiority of our proposed encoding–decoding combination, which achieves better performance in terms of the peak SNR, structural similarity index measure, and visual effects.