| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 562447 | Signal Processing | 2015 | 7 Pages |
•A novel noise model of digital image pixel׳s is proposed.•The heteroscedastic model for RAW image is extended to rendered images.•This model is shown to outperform the state-of-the-art models.•A simple yet efficient method for parameters estimation is also proposed.•An application for denoising of digital still images in also presented.
The goal of this paper is to propose a generalized signal-dependent noise model that is more appropriate to describe a natural image acquired by a digital camera than the conventional Additive White Gaussian Noise model widely used in image processing. This non-linear noise model takes into account effects in the image acquisition pipeline of a digital camera. In this paper, an algorithm for estimation of noise model parameters from a single image is designed. Then the proposed noise model is applied with the Local Linear Minimum Mean Square Error filter to design an efficient image denoising method.
