Illumination Map Estimation via Sparse Bright Channel for Enhancing Under-Exposed Images

This paper presents a novel image enhancement approach to avoid common artifacts such as over-exposure, color cast, and unnatural results. The key innovation lies in estimating the illumination map of an underexposed image using a sparse bright channel. Our approach includes an algorithm that enforces the sparsity of the inverted bright channel, enabling the indirect estimation of a coarse but suitable initial illumination map. This initial map is refined using an updated weight-constrained regularization with joint local exposure and detail feedback constraints, producing a piece-wise smooth, structure-preserving illumination map. Computer simulations show that the proposed method is competitive with or even outperforms several state-of-the-art enhancement methods in terms of both subjective and objective evaluations.