Estimation of image noise using polynomial masks
Albert Akhriev, Alexander Bonch-Osmolovsky · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2004
Many computer vision and image processing algorithms rely on the knowledge of the image noise variance as their input parameter. However, in practice, the distinction between noise and image features is not easy to draw. In this paper, image noise variance is estimated by a novel method employing rigorously derived polynomial masks. The method is based on the assumption that the image can be locally represented as a polynomial of the given degree and constitutes a generalization of some of previously proposed approaches.