Noise Estimation and Multiresolution Reconstruction for Dental Panoramic X-ray Images

This thesis presents a new approach to the reconstruction of dental panoramic x-ray images with experimental results. The reduction of the x-ray dose that offers higher safety for the patient reduces diagnostic image quality. Inverse filtering often fails due to insufficient knowledge about the noise, which varies depending on the location. In order to overcome the aforementioned obstacles, the method proposed in this thesis firstly develops a semi-empirical scatter-glare model of the photon projection process and applies it to the auto computation of an appropriate noise-estimate. Secondly, the energy of the noise-estimate is then subtracted from that of the diagnostic image in the different resolution levels of a Multiresolution Decomposition. Experiments show that the method outperforms state-of-the-art denoising in terms of better modulation transfer function and signal to noise ratio.