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首页> 外文期刊>IEEE Transactions on Circuits and Systems for Video Technology >Combined spatial and temporal domain wavelet shrinkage algorithm for video denoising
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Combined spatial and temporal domain wavelet shrinkage algorithm for video denoising

机译:结合时空域小波收缩算法进行视频降噪

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A combined spatial- and temporal-domain wavelet shrinkage algorithm for video denoising is presented in this paper. The spatial-domain denoising technique is a selective wavelet shrinkage method which uses a two-threshold criteria to exploit the geometry of the wavelet subbands of each video frame, and each frame of the image sequence is spatially denoised independently of one another. The temporal-domain denoising technique is a selective wavelet shrinkage method which estimates the level of noise corruption as well as the amount of motion in the image sequence. The amount of noise is estimated to determine how much filtering is needed in the temporal-domain, and the amount of motion is taken into consideration to determine the degree of similarity between consecutive frames. The similarity affects how much noise removal is possible using temporal-domain processing. Using motion and noise level estimates, a video denoising technique is established which is robust to various levels of noise corruption and various levels of motion.
机译:提出了一种结合时空域的小波收缩算法进行视频降噪。空域降噪技术是一种选择性的小波收缩方法,它使用两个阈值标准来开发每个视频帧的小波子带的几何形状,并且图像序列的每个帧都在空间上彼此独立地进行降噪。时域降噪技术是一种选择性的小波收缩方法,可估计噪声破坏的程度以及图像序列中的运动量。估计噪声量以确定在时域中需要多少滤波,并考虑运动量以确定连续帧之间的相似度。相似性影响使用时域处理可以去除多少噪声。使用运动和噪声水平估计,建立了一种视频降噪技术,该技术对各种级别的噪声破坏和各种级别的运动都具有鲁棒性。

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