| Ghost imaging is a novel imaging technique that has attracted much attention in recent years.Compared to traditional ghost imaging,computational ghost imaging not only has a simpler optical path,but also can improve the image quality by artificially designing the illumination pattern.As the development of computational ghost imaging technology becomes more and more sophisticated,it is gradually moving towards practical applications.However,because it requires long time for sampling,the sampling process is susceptible to the problem of missing sampling information by external interference,resulting in a significant decline in the final imaging quality,which restricts the further development of the technology.Therefore,to address the problem of missing sampling information in computational ghost imaging due to external influences,this thesis introduces wavelet transform and wavelet image fusion techniques into the computational ghost imaging system.First,the wavelet function is used to construct an illumination pattern to irradiate the target object for multiple sampling to obtain multiple sets of measurement bases.Then,the wavelet image fusion method was chosen to introduce into the computational ghost imaging system method to fuse multiple sets of wavelet coefficients.Finally,the wavelet function is used for computational ghost imaging reconstruction to obtain high-quality target images.The simulation and experimental study of this problem according to the above steps show the effectiveness of this system,which is more suitable for practical application environment than the traditional computational ghost imaging system. |
