Poisson Gaussian Noise

Poisson-Gaussian noise, a prevalent type of image noise combining Poisson and Gaussian components, is a significant challenge in image processing, particularly in low-light imaging and microscopy. Current research focuses on developing accurate noise parameter estimation methods, often leveraging paired noisy and clean image data, and employing advanced denoising algorithms such as diffusion models and those based on cumulant statistics or adaptive loss functions to mitigate the noise while preserving image detail. These improvements in noise modeling and denoising techniques are crucial for enhancing the quality of images across various applications, including medical imaging, astronomy, and computational photography.