Gray-level grouping (GLG): an automatic method for optimized image contrast Enhancement-part I: the basic method

By Zhiyu Chen, Besma Roui-Abidi, David L. Page, Mongi A. Abidi. IEEE Transactions on Image Processing, 2006

329 citations recorded by the source corpus.

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Contrast Enhancement Based on Layered Difference Representation of 2D Histograms (2013, methodology): “Fourth, PixDist computes the average gray-level difference over all pixel pairs in an image.”
An Experiment-Based Review of Low-Light Image Enhancement Methods (2020, background): “…the no-reference image quality metric for contrast distortion (NIQMC) [294], the Global Contrast Factor (GCF) [295], the average information content (AIC) [296], the effective measure of enhancement (EME) [297], PixDist [298], and the no-reference free-energy-based robust metric (NFERM) [299].”
MBLLEN: Low-Light Image/Video Enhancement Using CNNs (2018, methodology): “To evaluate the performance of different methods from different aspects and in a more fair way, we use a variety of different metrics, including PSNR, SSIM [39], Average Brightness(AB) [6], Visual Information Fidelity(VIF) [32], Lightness order error(LOE) as suggested in [41] and TMQI [40].”