Video speckle noise reduction using robust diffusion tensor in shearlet domain

Olfa Moussa, Nawrès Khlifa
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引用次数: 2

Abstract

We proposed a novel method of video speckle noise reduction by exploiting the sparse geometric image representation property of the Shearlet transform and the 3D Tensor-based Anisotropic Diffusion technique. The performance of the proposed method is evaluated and compared with VIDOLSAT filter on synthetic and real data. By using full reference image quality assessment and no reference image quality assessment the experimental results demonstrate that the proposed algorithm promising despeckling results and can realize better preserved edges.
基于剪切波域鲁棒扩散张量的视频散斑噪声抑制
利用Shearlet变换的稀疏几何图像表示特性和基于三维张量的各向异性扩散技术,提出了一种新的视频散斑降噪方法。在合成数据和实际数据上对该方法的性能进行了评价,并与VIDOLSAT滤波器进行了比较。通过完全参考图像质量评估和不进行参考图像质量评估的实验结果表明,该算法具有良好的去斑效果,可以实现更好的边缘保留。
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