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The State of the Art in HDR Deghosting: A Survey and Evaluation., , , и . Comput. Graph. Forum, 34 (2): 683-707 (2015)An Objective Deghosting Quality Metric for HDR Images., , , и . Comput. Graph. Forum, 35 (2): 139-152 (2016)Application of context invariants in airport region of interest detection for multi-spectral satellite imagery., , и . SIU, стр. 1-4. IEEE, (2012)Learning Foveated Reconstruction to Preserve Perceived Image Statistics., , , , , и . CoRR, (2021)Why Are Deep Representations Good Perceptual Quality Features?, , , и . ECCV (22), том 12367 из Lecture Notes in Computer Science, стр. 445-461. Springer, (2020)Luminance-contrast-aware foveated rendering., , , , , , и . ACM Trans. Graph., 38 (4): 98:1-98:14 (2019)Consistent Filtering of Videos and Dense Light-Fields Without Optic-Flow., , , , , , и . VMV, стр. 125-134. Eurographics Association, (2019)A Perception-driven Hybrid Decomposition for Multi-layer Accommodative Displays., , , , , , , , , и . IEEE Trans. Vis. Comput. Graph., 25 (5): 1940-1950 (2019)Stimulating the Human Visual System Beyond Real World Performance in Future Augmented Reality Displays., , , , , и . ISMAR, стр. 90-100. IEEE, (2020)The State of the art in HDR deghosting and an objective HDR image deghosting quality metric ; YDA görüntü gölgeleme gidermede gelişmişlik seviyesi ve YDA görüntüler için nesnel bir gölgeleme giderme kalite metriği.. Middle East Technical University, Çankaya, Ankara, Turkey, (2016)base-search.net (ftmetuankair:oai:open.metu.edu.tr:11511/25420).