由于实时目标的红外图像具有信噪比低、边界模糊等问题,在研究红外图像噪声特点的基础上,提出了一种基于动静态检测算法的红外图像降噪算法.通过一种动静态检测算法将图像分成动态图像和静态图像,用改进的自适应维纳滤波算法处理动态图像,用改进的NL-means降噪算法处理静态图像,并用FPGA实现红外图像降噪系统设计.实验表明,红外图像经算法处理后,其PSNR和细节方差-背景方差比(DV/BV)均高于经典降噪算法,算法能有效减少图像噪声,并能很好地保持图像的边界细节信息.%For the low SNR and contrast and the fuzzy edge in infrared image,a new noise reduction algorithm based on motion detection is proposed. The property of the noise of infrared image is analysed and image is divided into motion image and still image through a motion detection algorithm. The motion image and the still image is processed by a improved self-adaptive Wiener filter algorithm and NL-means algorithm .The noise reduction system is implemented by FPGA. The experiment shows:the PSNR and DV/BV of image both are higher than traditional algorithm after being disposed with the algorithm. And the algorithm can effectively reduce noise and dissolve the problem of image edge blur.
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