Image reconstruction algorithms in single pixel camera - Zhang, Yige (2019)
In 2006, Marco F. Duarte et al successfully designed a single-pixel camera based on compressed sensing (CS) and optical imaging. Single-pixel camera strictly satisfies compressed sensing theory, verifies its correctness, and breaks traditional development mode of modern camera that pursues sensor chips with huge amount of pixels. Instead, by only adopting single-photon detector high-quality images can be constructed, where required data is much smaller than the original image information. The development of digital camera is no longer limited to the size of electronic sensors thanks to the Single-pixel sensing and imaging technology. Apart from compressed sensing, undersampling using a transform basis has also proven its feasibility in image restoration with small number of measurements. Based on these two main methods, numerous algorithms that enhance the recovery efficiency have emerged. Single-pixel camera has attracted much attention because of many unique advantages, and has become one of the trends of future digital camera development. Aiming at the in-depth study of image reconstruction in single-pixel camera, this thesis mainly covers the following aspects: (1) Introduction on principles of single-pixel camera and reconstruction algorithms. (2) Comparisons by simulation between Discrete Cosine Transform (DCT) and Hadamard Transform (HT), along with optimization algorithms in undersampling and compressive sensing. (3) Principles of a novel algorithm: adaptive wavelet acquisition, and performance convincing data is provided. (4) Robustness testing on every above image restoration method. (5) Results of implementing adaptive wavelet algorithm in realistic experiments.