Patch-based Video Denoising with Optical Flow Estimation

Abstract

Over the years a variety of methods have been introduced to remove noise from digital images, such
as Gaussian filtering, anisotropic filtering, and Total Variation minimization. However, many of these
algorithms remove the fine details and structure of the image in addition to the noise because of assumptions
made about the frequency content of the image. The non-local means algorithm does not make these
assumptions, but instead assumes that the image contains an extensive amount of redundancy. These
redundancies can then be exploited to remove the noise in the image. This project will implement the non-local
means algorithm and compare it to other denoising methods using the method noise measurement.