Parallel computing of layer-based method for generating hologram of 3D objects is introduced. 3D MAX is used to model 3D object. The hologram of 3D model with depth information is calculated by Fresnel diffraction algorithm. The computational hologram generated by computer is reconstructed photoelectric to verify the correctness of the algorithm. This paper expounds the hardware architecture of GPU and CPU, briefly introduces the bottleneck and solution of CPU and GPU acceleration, and describes the optimization of thread and storage bandwidth in parallel processing. We use GPU hardware parallel computing and optimize the calculation process of 3D object hologram by using MKL and CUDA computing environment to improve the efficiency of computing. After analysis, the results show that the parallel computing speed of GPU hardware is 63 times faster than CPU alone. The parallel acceleration method can greatly shorten the computing time of generating hologram with layer-based method.
The radio frequency interference (RFI) has an adverse effect on the useful signals, which can degrade the image quality seriously. An improved eigensubspace-based approach for RFI filtering of synthetic aperture radar images is developed. In the preprocessing stage of the proposed approach, the data sets that need subsequent processing can be selected in both frequency and time domain. Then, the data can be processed by the traditional eigensubspace-based approach. Compared with the traditional eigensubspace-based approach, our approach can work more efficiently and effectively.