This work presents a comprehensive analysis of how extreme data quantization and fixed pattern noise (FPN) from CMOS imagers affect the performance of deep neural networks for image recognition tasks.

The expanding use and importance of image sensors in safety-critical applications such as automotive and medical devices has transformed noise from an annoyance into a life-threatening problem that ...

In recent years, Convolutional Neural Networks (CNNs) have achieved remarkable success in various computer vision tasks, including image denoising. Image denoising focuses on reconstructing a clean ...