Noise is present in all images captured by image sensors. Due to photon emission and photoelectric effects that are the foundations of the ways in which quantum mechanics enable image sensors, in fact, random noise is a “necessary evil” of image sensors that will continue to require our attention. The goal of this work is to provide a comprehensive characterization of random noise in ways that enhance post-image-capture signal processing steps. We derive the Poisson approximation to model the measurement noise that is the result of photon arrival and photon recapture. A novel methodology to learn the parameters that describe the noise is developed. We conclude by presenting preliminary evidence that accurate noise modeling would improve image denoising, especially in the low photon count/high noise regimes.
Xiaodan Jin, Zhenyu Xu Keigo Hirakawa, “Noise Parameter Estimation for Poisson Corrupted Images,” under review. [bibtex][pdf]