Fast And Robust Recursive Filter for Image Denoising
Fast And Robust Recursive Filter for Image Denoising
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DOI：
10.1109/icassp.2018.8461887
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发表时间：
2018-04
期刊：
影响因子：
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通讯作者：
Yiheng Chi;Stanley H. Chan
中科院分区：
文献类型：
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作者：
Yiheng Chi;Stanley H. Chan
移动的相机上的图像去噪要求低复杂度，但是许多最先进的去噪方法是计算密集型的。我们提出了一种低复杂度的去噪算法，使用边缘感知递归滤波器（RF）。我们做了两个贡献。首先，我们修改了原始RF，以便在从噪声输入中估计梯度时显着更鲁棒。我们扩展的RF高阶纹理和重噪声图像。其次，我们介绍了一种基于SURE的图像融合技术。我们表明，虽然个别RF有不同的性能，融合的结果往往是更好的。实验结果表明，新的RF执行速度比其他降噪，同时提供良好的图像质量。
Image denoising on mobile cameras requires low complexity, but many state-of-the-art denoising methods are computationally intensive. We present a low complexity denoising algorithm using an edge-aware recursive filter (RF). We make two contributions. First, we modify the original RF so that it is significantly more robust when estimating the gradients from noisy inputs. We extend the RF to high-order for texture and heavy noise images. Second, we introduce a SURE-based image fusion technique. We show that while individual RFs have different performance, the fused result is often better. Experimental results show that the new RF performs much faster than other denoisers while providing good quality images.