To explore the effect of applying multi-layer convolutional neural network to noise removal during the acquisition and transmission of functional motion images, the classical image denoising algorithms of mean filtering, median filtering, and wavelet transform filtering are first introduced. In addition, the evaluation methods of mean square error (MSE), image enhancement factor (IEF), peak signal to noise ratio (PSNR) and structural similarity measure (SSIM) in the image quality evaluation index system are introduced. Based on the convolutional neural network model, a multi-scale parallel convolutional neural network (MP-CNN) model is constructed to remove the noise in the image, and the functional action image is devoted to different degrees. Finally, the denoising effect is evaluated by the objective and subjective evaluation system. The objective evaluation results show that MP-CNN's MSE, IEF, PSNR, and SSIM are better than the single-channel model, and the test time is shorter. The subjective evaluation results show that the MP-CNN model has the best effect on noise removal after 25 denoising of functional action images. In this study, a multi-channel image denoising model based on the multi-layer convolutional neural network can improve the effect of functional motion image noise removal. KEYWORDSMulti-layer convolutional neural network, Functional action-image, Noise, Evaluation system METHODOLOGY Image denoising algorithmNoise generally has the characteristics of random distribution, and the probability density function can be used to describe the noise distribution, which can be divided into Gaussian, Rayleigh, exponent, γ, uniform and impulse noise and so on. The classical denoising methods include mean filtering, median filtering and wavelet transform filtering. Mean filtering is a common spatial linear filtering method, which plays an obvious role in smoothing noise, and the Box template is often used to filter noise images.

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The RF Linear Accelerator Free Electron Laser is usually operated in the oscillator mode. For high power operation, a ring resonator configuration with grazing angle incidence optics is the preferred choice. In this paper, we describe the modeling of such an oscillator configuration using full wave optics. The steady state mode structure of the resonator is obtained using Fox-Li type of calculation. We start with a gaussian field and propagate this field through the wiggler and the optical components of the resonator. The field at the end of one iteration through the resonator is compared with the field at the start of the iteration. This process is repeated until the field shape and the cavity power levels reach steady state reproducibility to within a couple of percent. The FEL interaction is modeled by tracking the motion of thousands of electrons through the wiggler and averaging their energy loss. Betatron motion of the electrons is taken into account as are any field and misalignment errors in the fabrication of the wiggler. We have used this numerical model to investigate the effects of (i) misalignment of mirrors, (ii) aberration of the mirrors, (iii) the efficacy of compensatory misalignment techniques, and (iv) the dependence of the performance of the FEL on the outcoupling fraction.

Time dependent propagation code simulations are described for phase compensation of atmospheric turbulence and thermal blooming. Test results, using convected phase screens to represent the optical turbulence, are compared with steady-state simulation results and, also, for fixed and variable direction wind conditions. Realistic wind effects on propagation are investigated by performing 4D code simulations to compare the effects of actual wind observations with monthly mean wind profile models for the White Sands Missile Range (WSMR). Critical power levels are compared for the mean and observed wind conditions at WSMR within the same month. Estimates of the critical power are also compared with the simulation results using the wind shear damping model for blooming instabilities, developed by Morris, et al., (SPIE Proc. flj, 229 (1990)).