Most cited papers in Image Enhancement Techniques
What are the most cited papers in Image Enhancement Techniques?
The most cited paper in Image Enhancement Techniques is "Perceptual Losses for Real-Time Style Transfer and Super-Resolution" (Justin M. Johnson, Alexandre Alahi, Li Fei-Fei, 2016), with 10,170 citations. Next come "Fast approximate energy minimization via graph cuts" (7,066) and "Making a “Completely Blind” Image Quality Analyzer" (6,737).
Showing 50 of 98 papers. Every paper with more than 1,300 citations is listed.
| # | Paper | ||
|---|---|---|---|
| 1 | Perceptual Losses for Real-Time Style Transfer and Super-Resolution Justin M. Johnson, Alexandre Alahi, Li Fei-Fei · Lecture notes in computer science | 2016 | 10,170 |
| 2 | Fast approximate energy minimization via graph cuts Yuri Boykov, Olga Veksler, Ramin Zabih · IEEE Transactions on Pattern Analysis and Machine Intelligence | 2001 | 7,066 |
| 3 | Making a “Completely Blind” Image Quality Analyzer A. Mittal, Rajiv Soundararajan, Alan Conrad Bovik · IEEE Signal Processing Letters | 14 Nov 2012 | 6,737 |
| 4 | Single Image Haze Removal Using Dark Channel Prior Kaiming He, Jian Cheng Sun, Xiaoou Tang · IEEE Transactions on Pattern Analysis and Machine Intelligence | 15 Sep 2010 | 6,281 |
| 5 | High-Speed Tracking with Kernelized Correlation Filters João F. Henriques, Rui Caseiro, Pedro Martins et al. · IEEE Transactions on Pattern Analysis and Machine Intelligence | Aug 2014 | 5,866 |
| 6 | "GrabCut" Carsten Rother, Vladimir Kolmogorov, Andrew Blake · ACM Transactions on Graphics | Aug 2004 | 5,822 |
| 7 | A universal image quality index Zhou Wang, Alan Conrad Bovik · IEEE Signal Processing Letters | Mar 2002 | 5,783 |
| 8 | Guided Image Filtering Kaiming He, Jian Zhong Sun, Xiaoou Tang · IEEE Transactions on Pattern Analysis and Machine Intelligence | 2 Oct 2012 | 5,494 |
| 9 | Fully-Convolutional Siamese Networks for Object Tracking Luca Bertinetto, Jack Valmadre, João F. Henriques et al. · Lecture notes in computer science | 2016 | 4,443 |
| 10 | Stereo Processing by Semiglobal Matching and Mutual Information Heiko Hirschmüller · IEEE Transactions on Pattern Analysis and Machine Intelligence | 20 Dec 2007 | 4,328 |
| 11 | Image information and visual quality Hamid R. Sheikh, Alan Conrad Bovik · IEEE Transactions on Image Processing | 18 Jan 2006 | 4,118 |
| 12 | Contrast Limited Adaptive Histogram Equalization Karel J. Zuiderveld · Elsevier eBooks | 1994 | 4,088 |
| 13 | Light field rendering Marc Levoy, Pat Hanrahan | Aug 1996 | 3,785 |
| 14 | DehazeNet: An End-to-End System for Single Image Haze Removal Bolun Cai, Xiangmin Xu, Kui Jia et al. · IEEE Transactions on Image Processing | 10 Aug 2016 | 3,386 |
| 15 | FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks Eddy Ilg, N. Michael Mayer, Tonmoy Saikia et al. | Jul 2017 | 3,369 |
| 16 | Colorful Image Colorization Richard Zhang, Phillip Isola, Alexei A. Efros · Lecture notes in computer science | 2016 | 3,362 |
| 17 | Selective Kernel Networks Xiang Li, Wenhai Wang, Xiaolin Hu et al. | Jun 2019 | 3,134 |
| 18 | Accurate, Dense, and Robust Multiview Stereopsis Yasutaka Furukawa, Jean Ponce · IEEE Transactions on Pattern Analysis and Machine Intelligence | Sep 2009 | 3,089 |
| 19 | A multiscale retinex for bridging the gap between color images and the human observation of scenes Daniel J. Jobson, Zia Ur Rahman, Glenn A. Woodell · IEEE Transactions on Image Processing | Jul 1997 | 3,055 |
| 20 | High Performance Visual Tracking with Siamese Region Proposal Network Bo Hu Li, Junjie Yan, Wei Wu et al. | Jun 2018 | 3,035 |
| 21 | A Statistical Evaluation of Recent Full Reference Image Quality Assessment Algorithms Hamid R. Sheikh, Muhammad Farooq Sabir, Alan Conrad Bovik · IEEE Transactions on Image Processing | 18 Oct 2006 | 3,027 |
| 22 | Color transfer between images Erik Reinhard, M. Adhikhmin, Bryan N S Gooch et al. · IEEE Computer Graphics and Applications | 2001 | 3,016 |
| 23 | LIME: Low-Light Image Enhancement via Illumination Map Estimation Xiaojie Guo, Yu Li, Haibin Ling · IEEE Transactions on Image Processing | 14 Dec 2016 | 3,001 |
| 24 | Learning Multi-domain Convolutional Neural Networks for Visual Tracking Hyeonseob Nam, Bohyung Han | Jun 2016 | 2,850 |
| 25 | EnlightenGAN: Deep Light Enhancement Without Paired Supervision Yifan Jiang, Xinyu Gong, Ding Liu et al. · IEEE Transactions on Image Processing | 2021 | 2,612 |
| 26 | RAFT: Recurrent All-Pairs Field Transforms for Optical Flow Zachary Teed, Jia Hao Deng · Lecture notes in computer science | 2020 | 2,596 |
| 27 | SiamRPN++: Evolution of Siamese Visual Tracking With Very Deep Networks Bo Li, Wei Wu, Qiang Wang et al. | Jun 2019 | 2,563 |
| 28 | A Fast Single Image Haze Removal Algorithm Using Color Attenuation Prior Qingsong Zhu, Jiaming Mai, Ling Shao · IEEE Transactions on Image Processing | 18 Jun 2015 | 2,500 |
| 29 | Image quilting for texture synthesis and transfer Alexei A. Efros, William T. Freeman | Aug 2001 | 2,416 |
| 30 | Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement Chunle Guo, Chongyi Li, Jichang Guo et al. | Jun 2020 | 2,406 |
| 31 | PVT v2: Improved baselines with pyramid vision transformer Wenhai Wang, Enze Xie, Xiang Li et al. · Computational Visual Media | 16 Mar 2022 | 2,391 |
| 32 | AOD-Net: All-in-One Dehazing Network Boyi Li, Xiulian Peng, Zhangyang Wang et al. | Oct 2017 | 2,370 |
| 33 | Properties and performance of a center/surround retinex Daniel J. Jobson, Zia Ur Rahman, Glenn A. Woodell · IEEE Transactions on Image Processing | Mar 1997 | 2,339 |
| 34 | Single-Image Crowd Counting via Multi-Column Convolutional Neural Network Yingying Zhang, Desen Zhou, Siqin Chen et al. | Jun 2016 | 2,326 |
| 35 | Benchmarking Single-Image Dehazing and Beyond Boyi Li, Wenqi Ren, Dengpan Fu et al. · IEEE Transactions on Image Processing | 30 Aug 2018 | 2,317 |
| 36 | Visibility in bad weather from a single image Robby T. Tan | Jun 2008 | 2,312 |
| 37 | Albumentations: Fast and Flexible Image Augmentations Alexander Buslaev, Vladimir I. Iglovikov, Eugene Khvedchenya et al. · Information | 24 Feb 2020 | 2,295 |
| 38 | A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation Nikolaus Mayer, Eddy Ilg, Philip Hausser et al. | Jun 2016 | 2,279 |
| 39 | Run, Don't Walk: Chasing Higher FLOPS for Faster Neural Networks Jierun Chen, Shiu-hong Kao, Hao He et al. | Jun 2023 | 2,270 |
| 40 | A Database and Evaluation Methodology for Optical Flow Simon J Baker, Daniel Scharstein, John P. Lewis et al. · International Journal of Computer Vision | 29 Nov 2010 | 2,263 |
| 41 | Saliency filters: Contrast based filtering for salient region detection Federico Perazzi, Philipp Krähenbühl, Yael Pritch et al. | Jun 2012 | 2,144 |
| 42 | Single image dehazing Raanan Fattal · ACM Transactions on Graphics | Aug 2008 | 2,137 |
| 43 | Pre-Trained Image Processing Transformer Hanting Chen, Yunhe Wang, Tianyu Guo et al. | Jun 2021 | 2,104 |
| 44 | U2Fusion: A Unified Unsupervised Image Fusion Network Han Xu, Jiayi Ma, Junjun Jiang et al. · IEEE Transactions on Pattern Analysis and Machine Intelligence | 28 Jul 2020 | 2,102 |
| 45 | Robust Object Tracking with Online Multiple Instance Learning Boris Babenko, Shuicheng Yan, Serge Belongie · IEEE Transactions on Pattern Analysis and Machine Intelligence | 23 Dec 2010 | 2,039 |
| 46 | DenseFuse: A Fusion Approach to Infrared and Visible Images Hui Li, Xiao-Jun Wu · IEEE Transactions on Image Processing | 18 Dec 2018 | 2,015 |
| 47 | Most apparent distortion: full-reference image quality assessment and the role of strategy Damon M. Chandler · Journal of Electronic Imaging | 2010 | 1,982 |
| 48 | LLNet: A deep autoencoder approach to natural low-light image enhancement Kin Gwn Lore, Adedotun Akintayo, Soumik Sarkar · Pattern Recognition | 17 Jun 2016 | 1,969 |
| 49 | Unsupervised Learning of Visual Features by Contrasting Cluster Assignments Mathilde Caron, Ishan Misra, Julien Mairal et al. · arXiv (Cornell University) | 17 Jun 2020 | 1,903 |
| 50 | MemNet: A Persistent Memory Network for Image Restoration Ying Yu Tai, Jian Jun Yang, Xiaoming Liu et al. | Oct 2017 | 1,894 |
Citations are OpenAlex's own counts, from its 2026-09-23 snapshot, so the ranking can differ from Google Scholar or Web of Science. A paper is listed for a field when OpenAlex files it under one of the field's topics; retracted papers and papers whose citation count cannot be traced to citing works are left out, and a preprint and the article it became are shown once. Release dates are OpenAlex's: where a source gave only a month or a year, that is what is shown. How the lists are chosen.