1.2022-Deep Learning Optimized Terahertz Single-Pixel Imaging
创新点：However, all these reports focus on reducing the sampling rate or the number of patterns M, but leave the sampling time per pattern t0 untouched.
观测矩阵：However, these compressed sensing algorithms adopt nonorthogonal random patterns, hindering further compression of the sampling ratio. To tackle this problem, deterministic model-based techniques, which adopt deterministic orthogonal basis patterns such as Hadamard patterns or Fourier patterns to encode the THz fields, and utilize matrix operations to reconstruct THz images, have been proposed recently.
算法：Most ghost imagingmodels based on deep convolutional neural networks do not make full use of the hierarchical features from the original low-quality images, thereby resulting in relatively-low performance.
2.2020-Broadband high-resolution terahertz single-pixel imaging(调制器调制深度100%)
观测矩阵：There are many methods to generate patterns for masking an object (with ON and OFF pixels that transmit and block the optical signal, respectively), including the Hadamard, Fourier , and Toeplitz methods. The generated masks should be orthogonal to each other and equally ON:OFF pixel weighted for faster reconstruction. However, pseudo-random pattern reconstruction methods, i.e., nonorthogonal patterns with a small number of new pixels per mask, have been proven to be as effective as those using fully random patterns.