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The technology of atomic layer deposition has been used to improve the lifetime of the microchannel plate-photomultiplier tube (MCP-PMT) effectively and makes MCP possible to choose to coat different potential emissive materials on the internal surface of the MCP channels in the future. However, it is still an open question to what extent the secondary electron emission (SEE) yield properties of the emissive materials influence the behavior of the ALD-coated MCP. In this work, the dependences of the gain and timing performance on the SEE yield properties were assessed by using the Monte Carlo and particle-in-cell methods. We established the three-dimensional MCP single channel model in Computer Simulation Technology (CST) Particle Studio. Three important secondary electron emissions, the backscattered, rediffused and true SEEs, were discussed numerically based on the probabilistic model. The secondary electron cascade processes in the MCP single channel were simulated. The simulation results indicate that the opportunities for improving the gain of the ALD-coated MCP by improving the SEE yields corresponding to the incident energies of 0 eV–100 eV. The backscattered and rediffused electrons are found to have strong effects on the gain and timing performance of the MCP. Although the higher the SEE yield the higher the MCP gain, the drawback is the extremely high SEE yield will make the MCP saturated prematurely and degrade the time resolution. The simulation results will be used to guide the design and selection of emissive material for ALD-coated MCP development.

In order to realize the real-time segmentation processing of multi-spectral images in practice, a real-time multi-spectral images segmentation system composed of four TMS320C6455 DSPs, two Virtex-4 aV4 XC4VLX80 aFPGAs and one Virtex-2 Pro a V2 Pro20 aFPGA is designed. Through the optimization of the cooperation processing of the multi-DSP and multi-FPGA, the parallel multi-task processing ability of the DSPs and the effective interf ace coordination ability of the FPGAs in the built system are used fully. In order to display the processing ability, the segmentation test experiments of 10 spectra visible images, with 1024×1024, segmented by the Multi-scale Image Segmentation Method, was done in the built multi-spectral images segment system. The experiment re sults prove that the multi-DSP and multi-FPGA multi-spectral images processing system designed in this paper satisfies the real-time processing requirement in engineering practice. Keywords: Multi-spectral Imagery, Image Segmentation, Multi-scale Image Segmentation Method, Multi-DSP, Multi-FPGA, Parallel Processing.

An ordinary space optical remote sensing camera is an optical diffraction-limited system and a low-pass filter from the theory of Fourier Optics, and all the digital imaging sensors, whether the CCD or CMOS, are low-pass filters as well. Therefore, when the optical image with abundant high-frequency components passes through an optical imaging system, the profuse middle-frequency information is attenuated and the rich high-frequency information is lost, which will blur the remote sensing image. In order to overcome this shortcoming of the space optical remote sensing camera, an online compensating approach of the Modulation Transfer Function in the space cameras is designed. The designed method was realized by a hardware analog circuit placed before the A/D converter, which was composed of adjustable low-pass filters with a calculated value of quality factor Q. Through the adjustment of the quality factor Q of the filters, the MTF of the processed image is compensated. The experiment results display that the realized compensating circuit in a space optical camera is capable of improving the MTF of an optical remote sensing imaging system 30% higher than that of no compensation. This quantized principle can efficiently instruct the MTF compensating circuit design in practice.

The distance regularized level set method has the advantage of maintaining the regularity of the level set function without re-initialization. However, it has the disadvantage of requiring the initial curve around or inside the detected objects. In this paper, an adaptive distance regularized level set method is designed. Firstly, the local energy term is introduced to make the method robust to how and where the initial curve is selected and can successfully segment the images with intensity heterogeneity. Secondly, a Gaussian filter is utilized to ensure the smoothness and regularity of the level set function and eliminate re-initialization. Furthermore, the narrow band method is applied in the adaptive distance regularized level set method to reduce the computation and the convergence time. The results of the comparative experiments show the advantages of the designed method.

It is very difficult to measure the distance of a moving point target which is not cooperative for detecting in the remote sensing field, because that the point target has no geometrical dimensions and textures can be used and is easy to be missed. In this paper, a new algorithm based on the image sequence and the nonlinear regressive filtering algorithm is proposed, in order to determine the 3-D parameters of the moving point target in an efficient passive way. And a new multi-channel optical imaging system is designed, which is composed of a high- resolution center imaging system and four low-resolution sub-imaging systems. By the geometrical relationship of the four sub-imaging system, the initial values of the nonlinear regressive filtering algorithm for estimating can be obtained easily. Finally, the experiments of the proposed algorithm have been done on a real system, and the results proved that the algorithm could passively obtain the 3-D parameters of the moving point target efficiently. Furthermore, in the estimating procedure, the character of the nonlinear regressive filtering algorithm saves lots of memory units and reduces the computing quantity.