Shallow Camera Pipeline for Night Photography Enhancement

Abstract

Enhancing night photography images is a challenging task that requires advanced processing techniques. While CNN-based methods have shown promising results, their high computational requirements and limited interpretability can pose challenges. To address these limitations, we propose a camera pipeline for rendering visually pleasing photographs in low-light conditions. Our approach is characterized by a shallow structure, explainable steps, and a low parameter count, resulting in computationally efficient processing. We compared the proposed pipeline with recent CNN-based state-of-the-art approaches for low-light image enhancement, showing that our approach produces more aesthetically pleasing results. The psycho-visual comparisons conducted in this work show how our proposed solution is preferred with respect to the other methods (in about 44% of the cases our solution has been chosen, compared to only about 15% of the cases for the state-of-the-art best method).