在静止场景下普通的图像滤波算法就能够有效抑制噪声，而在运动状态下，现有的滤波算法难以保证去噪的有效性，还会产生拖尾现象；采用运动补偿的滤波算法，又无法有效地抑制噪声。针对以上问题，提出一种基于时空域滤波的视频去噪算法，并在现场可编程逻辑门阵列（Field Programmable Gate Array，FPGA）平台上实现。该算法主要运用高斯差分滤波提取图像特征，再用空域滤波抑制高频噪声，采用反馈的方式对分割出的图像区域采用不同的去噪策略。硬件实现的关键是利用高层次综合（High-level Synthesis，HLS）工具简化编程、DDR3控制模块操作视频流在各模块间输入输出。实验结果表明：该算法能有效去噪，不同场景下，相比基于非下采样轮廓波变换的去噪算法，峰值信噪比最多可提升15 dB；将算法移植到FPGA后，峰值信噪比相比于MATLAB软件仿真相差约0.3 dB，运行时间缩短71.5%以上，在兼顾实时性的同时达到了较好的可见光视频去噪效果。

It is difficult to suppress the noise in static state of the existing filtering algorithm. Moreover， motion compensated filtering algorithm fails to effectively suppress noise. To solve these problems， a video denoising algorithm based on spatio-temporal filtering is proposed and implemented on the field programmable gate array （FPGA）. The algorithm mainly uses Gaussian difference filtering to extract image features， and then applies spatial filtering to suppress high-frequency noise. Simultaneously， different denoising strategies are adopted for the segmented image area by feedback. Implementing hardware requires high-level synthesis tools to simplify programming， and is to make DDR3 control module to operate input and output of video stream between modules. Simulation results show that the proposed algorithm can be used for denoising. For different scenes， the peak signal-to-noise ratio can be increased by up to 15 dB in comparison with the denoising algorithm based on a non-subsampled contourlet （NSCT）. After transplanting the algorithm to FPGA， the difference between PSNR and MATLAB simulation program was approximately 0.3 dB， and the running time was shortened by over 71.5%. Considering the real-time performance， PSNR achieves a better visible video denoising effect.