传统的视频降噪滤波在空域或者时域中进行,若视频中的噪声过大,其滤波效果较差。最新的有着较高性能的BM3D算法必须进行块匹配处理,且对于部分有着平滑过渡色彩的图像并不适合。基于双域滤波算法提出了一种改进的算法,其更加适合视频降噪。通过空域和频域分别对分层图像进行降噪, 有效地滤除 大噪点和小噪点,在时域上的双边滤波不仅提高了滤除噪声的能力,而且更好地保留了图像边缘特征。仿真实验表明,改进的双域滤波视频降噪算法在PSNR值上较DCT算法提高了约1dB,与原双边滤波算法相比,无论是在主观视觉还是客观评价上,所提算法均有较好效果及优势。
Image denoising continues to be an active research topic.Recently the proposed BM3D is based on block matching,which introduces visible artifacts in homogeneous regions,manifesting as low-frequency noise.This paper offered a hybrid method that is easy to implement and yet rivals BM3D in quality.The noise differentials were estimated using robust kernels in two spatial domains,one spatial range domain and one frequency range domain.The approach using robust estimators unifies spatial and wavelet domain methods.Video denoising based on temporal is highly effective,and the method is further demonstrated particularly to be suitable for video denoising.Comparing to the DCT,the value of PSNR of the proposed method is improved by about 1dB.