A Novel Image Noise Level Function Estimation Approach using Camera Response Function Constraint

Abstract

Abstract. In this paper, we propose a noise level evaluation method for real captured photos. Different from conventional noise removal methods that assume noise follow a simply additive Gaussian distribution, noise distribution in our method is supposed to be a more sophisticated intensity-dependent distribution, which has a better fit with actual noise model. Follow the definition of noise level function (NLF) which represents the variation of the standard deviation of noise with respect to image intensity. After exposing the close relationship between NLF and camera response function (CRF), we fit the curve of NLF with the constraints imposed by the shape of CRF.

Real‐Time Noise Source Estimation of a Camera System from an Image and Metadata

“…[22][23][24] To account for nonlinear camera processes that affect noise statistics, [25] some works employ the camera response function for NLF estimation; they describe a camera's physical processing as a black box in a single function. [26,27] A few noise studies break down the noise caused by camera electronics and therefore consider more than two noise sources, [7,[28][29][30] but generally "[…] noise sources caused by digital camera electronics are still largely overlooked, despite their significant effect on raw measurement". [28] The works in refs.…”

“…[ 22–24 ] To account for nonlinear camera processes that affect noise statistics, [ 25 ] some works employ the camera response function for NLF estimation; they describe a camera's physical processing as a black box in a single function. [ 26,27 ]…”