Denoising an image by denoising its curvature image
SIAM Journal on Imaging Sciences
Curvature, Image denoising, Image reconstruction
In this article we argue that when an image is corrupted by additive noise, its curvature image is less affected by it; i.e., the peak signal-to-noise ratio of the curvature image is larger. We speculate that, given a denoising method, we may obtain better results by applying it to the curvature image and then reconstructing from it a clean image, rather than denoising the original image directly. Numerical experiments confirm this for several PDE-based and patch-based denoising algorithms. © 2014 Society for Industrial and Applied Mathematics.
Bertalmío, M., & Levine, S. (2014). Denoising an image by denoising its curvature image. SIAM Journal on Imaging Sciences, 7 (1), 187-211. https://doi.org/10.1137/120901246