Automatic Highly Accurate Estimation of Gaussian Noise Level in Digital Images Using Filtration and Edges Detection Methods

Abstract

Abstract-In this paper we propose a highly accurate method of automatically estimation of the Gaussian noise level in digital images, which is based on image filtering and analysis of the region of interest. Noise level is an important parameter to many digital image processing applications, for example, when removing noise. As the noise level its standard deviation is calculated.

Gaussian noise parameter estimation based on multiple singular value decomposition and non‐linear fitting

“…The fact that (𝜎, b) satisfies the incremental Equation ( 14) is both a sufficient and necessary condition for solving Equation (11). Finally, the iterative formula of the Gauss-Newton iteration method is…”

“…To optimize the performance of the estimator, some scholars try to use multiple filters together. Balovsyak [11] utilizes high‐pass filtering to retrieve the noise components and low‐pass filtering to pick the effective regions containing noise.…”