Power-constrained image contrast enhancement is a fundamental step for improving the battery life of modern consumer devices with embedded emissive-display panels, such as organic light-emitting diodes (OLEDs). The conventional power constrained image contrast enhancement in OLED displays is typically performed using histogram-relevant priors or heuristic curve-fitted techniques. This results in underexposure effects or color-tone changes in the reconstructed image. Therefore, this paper proposes a novel power-constrained sparse representation model by joint l2, 1, γ, and isotropic total variation norm (called mixed-norm) regularized sparse coding to simultaneously improve power saving and the perceptible visual quality of the OLED displays. The qualitative and quantitative experiments demonstrate that the proposed technique noticeably outperforms the state-of-the-art power-constrained contrast enhancement techniques.
GPU Accelerated PCSR implementation in Python: [GitHub]
J. Yin, B. Chen, E. Lai and L. Shi, "Power-constrained Image Contrast Enhancement through Sparse Representation by Joint Mixed-norm Regularization," IEEE Transactions on Circuits and Systems for Video Technology. vol. 30, no. 8, pp. 2477-2488, Aug. 2020. [pdf][bib]