[Research on Properties of Light Scattering for Non-Spherical Suspended Particles in Water Based on T Matrix Model].

Scattering light properties of suspended particles in water is an important parameter which influences the accuracy of water quality measurement. In this paper, based on T matrix model, the authors study the UV-Visible light irradiation intensity of 3 kinds of non-spherical suspended. particles including ellipsoid, cylinder and generalized Chebyshev in water. The relationship between light scattering intensity and incident light wavelength, shape parameters of suspended particles, complex refractive index and rotation angle has been presented in detail. Simulation results show that when changing the particle size, adjusting the wavelength of incident light, all light scattering intensity of 3 kinds of non-spherical suspended particles show significant changes. In the wavelength range from 200-800 nm, the impact of geometric on the particles size decreases with increasing wavelength and the sattering properites mainly depends on complex refractive index. The scattering intensity becomes stronger and exhibits strong oscillations for ultraviolet and infrared light when the diameter of particles are less than 0.2 µm or approaching 1 µm. However, the scattering intensity is relatively stable and close to zero, shows small disturbances with the change of wavelength of incident light when the particles sizes are within 0.3 to 0.9 µm.

A CT reconstruction algorithm based on non-aliasing Contourlet transform and compressive sensing.

Compressive sensing (CS) theory has great potential for reconstructing CT images from sparse-views projection data. Currently, total variation (TV-) based CT reconstruction method is a hot research point in medical CT field, which uses the gradient operator as the sparse representation approach during the iteration process. However, the images reconstructed by this method often suffer the smoothing problem; to improve the quality of reconstructed images, this paper proposed a hybrid reconstruction method combining TV and non-aliasing Contourlet transform (NACT) and using the Split-Bregman method to solve the optimization problem. Finally, the simulation results show that the proposed algorithm can reconstruct high-quality CT images from few-views projection using less iteration numbers, which is more effective in suppressing noise and artefacts than algebraic reconstruction technique (ART) and TV-based reconstruction method.