Combining the power of internal and external denoising

Maria Zontak
Michal Irani
Computational Photography (ICCP), 2013 IEEE International Conference on, pp. 1-9 (to appear)


Image denoising methods can broadly be classified into two types: “Internal Denoising” (denoising an image patch using other noisy patches within the noisy image), and “External Denoising” (denoising a patch using external clean natural image patches). Any such method, whether Internal or External, is typically applied to all image patches. In this paper we show that different image patches inherently have different preferences for Internal or External denoising. Moreover, and surprisingly, the higher the noise in the image, the stronger the preference for Internal Denoising. We identify and explain the source of this behavior, and show that Internal/External preference of a patch is directly related to its individual Signal to-Noise-Ratio (“PatchSNR”). Patches with high PatchSNR (e.g., patches on strong edges) benefit much from External Denoising, whereas patches with low PatchSNR (e.g., patches in noisy uniform regions) benefit much more from Internal Denoising. Combining the power of Internal or External denoising selectively for each patch based on its estimated PatchSNR leads to improvement in denoising performance.

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