Back to the Future: A Night Photography Rendering ISP Without Deep Learning

Simone Zini, Claudio Rota, Marco Buzzelli, Simone Bianco, Raimondo Schettini; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2023, pp. 1465-1473

Rendering night photography pictures is a challenging task that requires advanced processing techniques. Although deep learning-based Image Signal Processing (ISP) pipelines have shown promising results, current limitations are set by the lack of proper nighttime image datasets, their high computational requirements, and low explainability. In this paper, we propose a traditional ISP pipeline for rendering visually pleasing photographs of night scenes. Our pipeline is comprised of various algorithms addressing the different challenges presented by night images, and it is characterized by a shallow structure, explainable steps, and a low parameter count, resulting in computationally efficient processing. Moreover, it does not require training data. Experiments show that our pipeline can produce more pleasing results compared to other deep learning-based ISP pipelines, as it won first place in people's choice track and third place in photographer's choice track in the NTIRE 2023 Night Photography Rendering Challenge.