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With the proliferation of sophisticated cameras in modern society, the demandfor accurate and visually pleasing images is increasing. However, the qualityof an image captured by a camera may be degraded by noise. Thus, someprocessing of images is required to filter out the noise without losing vitalimage features. Even though the current literature offers a variety ofdenoising methods, the fidelity and efficacy of their denoising are sometimesuncertain. Thus, here we propose a novel and computationally efficient imagedenoising method that is capable of producing accurate images. To preserveimage smoothness, this method inputs patches partitioned from the image ratherthan pixels. Then, it performs denoising on the manifold underlying thepatch-space rather than that in the image domain to better preserve thefeatures across the whole image. We validate the performance of this methodagainst benchmark image processing methods.

A Patch-based Image Denoising Method Using Eigenvectors of the Geodesics' Gramian Matrix