一种基于自适应空间和运动补偿时间滤波器的智能视频降噪方法

Thou-Ho Chen, Chao-Yu Chen, Tsong-Yi Chen, Ming-Kun Wu
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引用次数: 1

摘要

本文针对高斯噪声和脉冲噪声对图像序列的干扰,提出了一种有效的降噪方法。其基本策略是将空间不明显失真与图像局部特征相结合进行空间滤波,利用运动补偿进行时间滤波。在空间滤波方面,提出了一种由谐波均值滤波、加权算术均值滤波、阿尔法均值滤波、中值滤波和阈值滤波组成的自适应滤波方案,用于去除图像中的噪声。然后,基于运动补偿的时间滤波器重点是利用前一帧和后一帧对经过空间滤波的图像帧进行细化。实验结果表明,该降噪方法对高斯噪声、固定值脉冲噪声和随机值脉冲噪声的平均信噪比分别提高了8.85%、11.69%和11.64%
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Intelliegent Video Noise Reduction Method Using Adaptive Spatial and Motion-Compensation Temporal Filter
In this paper, we propose an effective noise reduction method for image sequences corrupted by the Gaussian noise or impulse noise. The basic strategy is to combine the spatial just noticeable distortion (JND) with local image characteristics for spatial filtering and utilize the motion compensation for temporal filtering. For spatial filtering, an adaptive scheme composed of the harmonic mean filter, weighted arithmetic mean filter, alpha-trimmed mean filter, median filter and thresholding filter is dedicated to reducing noises on an image. Then, a motion-compensation based temporal filter is focused on refining the spatial-filtered image frame with the previous and following frames. Experimental results show that the proposed noise-reduction method is better than four previous methods with a PSNR improvement rate of 8.85% on Gaussian noise, 11.69% on fixed-value impulse noise and 11.64% on random-value impulse noise over the average of these four methods
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