Adaptive Low-Light Image Enhancement Selection Using Random Forest: Validation on ExDark Dataset with BRISQUE Quality Assessment
Low-light image enhancement remains challenging for resource-constrained edge devices where deep learning models are often too computationally expensive. This research presents an adaptive selection framework that learns to choose between two complementary enhancement strategies—a lightweight logarithmic boost and a so...