Compressive Correlated Imaging With Thermal Light

Correlated imaging, also called ‘ghost imaging’, offers great potentiality, with respect tostandard imaging, to obtain the imaging of objects located in optically harsh or noisy environment.It can solve the problems which are difficult to solve by standard imaging techniques. Recently, ithas become one of the hot topics in quantum optics. Traditional correlated imging still has someproblems in the realization process, such as large sampling times, long imaging time and lowimaging quality. The correlated imaging schemes based on compressive sensing can improve theefficiency of the correlated imaging with high imaging quality, is a good reference of in practicaluse.First of all, this thesis introduces the physical nature of the traditional correlated imagingscheme and the theory of compressive sensing in detail. Later, Taking advantage of the highsignal-to-noise ratio of the differential correlated imaging and low sampling frequency of thecompressive sensing technique, a new scheme based on differencial correlated imaging scheme isproposed, named differential compressive correlated imaging. In the new scheme, Gaussiandistribution matrix from the intensity of the thermal light is used as the measurement matrix ofcompressive sensing. Orthogonal matching pursuit algorithm is adopted as the recovery algorithm,and the object information is retrieved as the image of the object differential information with highquality. The results show that the scheme improves the Signal-to-Noise rate of the correlatedimaging greatly while has a reducing imaging time.Next, a compressive correlated imaging scheme based on the conditioned partial measurementsis presented. Two kinds of gray-scale images are selected as the example, such as ‘double-slit’ and‘NUPT’, as well as the two multi-grayscale images (Lena and Boats). The image quality is verifiedby the numerical simulation with the double efficiency and50%measurement data.At last, a combination of reference arm differential and compressive sensing is used to analysethe correlated imaging, named reference arm differential compressive correlated imaging scheme.The numerical results show that the new correlated imaging schemes can not only reduce thenumber of samples, measurement data, and the imaging time, but also improve the quality ofcorrelated imaging. It is an supplement to the the differential correlated imaging.In summary, this thesis presents some compressive correlated imaging schemes. They could allreduce the imaging time and improve the imaging quality to different degrees.