Image Enhancement Techniques
Image Enhancement Techniques is a research topic within Computer Vision and Pattern Recognition. Science Explorer counts 28k research works in it since 1950. 16.1% of them reached the world's top 10% most cited for their field and year.
This cluster of papers focuses on the advancements in image enhancement techniques, including dehazing, contrast enhancement, and color transfer. It covers a wide range of topics such as underwater imaging, single image restoration, low-light enhancement, and high dynamic range imaging. The cluster showcases the application of deep learning methods in addressing challenges related to image processing and enhancement.
- Dehazing
- Contrast Enhancement
- Image Processing
- Underwater Imaging
- Single Image Restoration
- Low-Light Enhancement
- Deep Learning
- Haze Removal
- Color Transfer
- High Dynamic Range
- Research works
- 28k fractional, since 1950
- In the world top 10%
- 4.5k per year above
- Top-10% rate
- 16.1% share of its works in the world top 10%
- Growth, 2013–17 → 2018–22
- +60% the tick is no change
Which countries lead Image Enhancement Techniques research?
By volume, China and India publish the most (5k and 902 works in 2022–2025).
By volume, 2022–2025
- 1 China 5k works
- 2 India 902 works
- 3 United States 408 works
- 4 South Korea 248 works
- 5 Japan 190 works
- 6 United Kingdom 148 works
- 7 Taiwan 127 works
- 8 Germany 97 works
- 9 ?? 95 works
- 10 Hong Kong 90 works
How concentrated that is
The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.
Shares of the rows listed above, not of the whole node.
Which institutions lead Image Enhancement Techniques research?
By volume in 2022–2025, Wuhan University publishes the most Image Enhancement Techniques research, followed by Beijing Institute of Technology and Northwestern Polytechnical University.
By volume, 2022–2025
- 1 Wuhan University China 66 works
- 2 Beijing Institute of Technology China 65 works
- 3 Northwestern Polytechnical University China 65 works
- 4 Chinese Academy of Sciences China 64 works
- 5 University of Science and Technology of China China 63 works
- 6 Dalian Maritime University China 60 works
- 7 Shanghai Jiao Tong University China 58 works
- 8 Xidian University China 57 works
- 9 Beihang University China 51 works
- 10 Nanjing University of Science and Technology China 49 works
Who are the leading researchers in Image Enhancement Techniques?
The most-cited researchers publishing on Image Enhancement Techniques include Wei Liu, Luc Van Gool and Alan Yuille.
- 1 Wei Liu 9.7k citations
- 2 Luc Van Gool 8.5k citations
- 3 Alan Yuille 8.4k citations
- 4 Xiaoou Tang 8k citations
- 5 Chen Change Loy 7.7k citations
- 6 Jiaya Jia 7.5k citations
- 7 Ming–Hsuan Yang 7.4k citations
- 8 Dacheng Tao 6.1k citations
Ranked by citations received across their whole record, among researchers with at least three works on this topic.
Where is Image Enhancement Techniques research done?
The largest centres of Image Enhancement Techniques research in 2022–2025 are Beijing (China), Shanghai (China), Xi'an (China) and Nanjing (China). Among places with at least 20 works in it, it is an unusually large share of all research in Dalian and Yantai.
Largest cities, 2022–2025
Where it is the local speciality
- DalianCN · 152.2 works7.3×
- YantaiCN · 32.3 works6.9×
Location quotient: how much more of its research is in Image Enhancement Techniques than the world average.
Where is the best place to study Image Enhancement Techniques?
Among universities, judged by research, Dalian Maritime University, Yunnan University and University of Science and Technology of China score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.
One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.
| # | University | Score | Top 10% | Specialisation | Works | Growth |
|---|---|---|---|---|---|---|
| 1 | Dalian Maritime University China | 80.7 | 29.6% | 20.4× | 60 | +211.2% |
| 2 | Yunnan University China | 71.5 | 23.1% | 11.1× | 34 | +259.3% |
| 3 | University of Science and Technology of China China | 71.3 | 30.4% | 6.5× | 63 | +163.4% |
| 4 | Wuhan University China | 71.0 | 34.5% | 6.8× | 66 | +97.8% |
| 5 | Xidian University China | 68.6 | 22.4% | 9.6× | 57 | +100.5% |
| 6 | Northwestern Polytechnical University China | 67.7 | 26.0% | 7.0× | 65 | +137.4% |
| 7 | Nanyang Technological University Singapore | 66.1 | 43.2% | 4.4× | 28 | +52.3% |
| 8 | City University of Hong Kong Hong Kong | 65.0 | 39.1% | 4.7× | 22 | +76.6% |
| 9 | Dalian University of Technology China | 64.8 | 28.0% | 5.5× | 42 | +252.9% |
| 10 | Changchun University of Science and Technology China | 63.2 | 12.7% | 20.3× | 37 | +195.0% |
Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.
Is Image Enhancement Techniques research growing?
Output in 2018–2022 was 60% higher than in 2013–2017, peaking in 2025. The fastest-growing topics are Image Enhancement Techniques.
The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.
Which topics inside it are moving
Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.