Exposure Correction in Driving Scenes Using the Atmospheric Scattering Model

The challenges posed by dynamic lighting conditions and unpredictable scenes necessitate robust image enhancement techniques. Grounded in the theoretical framework of the atmospheric scattering model, our study introduces a novel image enhancement approach that leverages deep learning and is reinforced by the integration of gamma correction. The obtained numerical results demonstrate a significant improvement over current state-of-the-art techniques, effectively enhancing object detection accuracy. Our method excels at addressing the complexity of real-world scenes and diverse lighting conditions, making it highly effective across diverse and demanding environments.