Image Processing Techniques and Applications
Image Processing Techniques and Applications is a research topic within Media Technology. Science Explorer counts 38k research works in it since 1950. 13.8% of them reached the world's top 10% most cited for their field and year.
This cluster of papers focuses on the development and evaluation of autofocusing algorithms for microscopy and digital cameras, with applications in depth estimation, shape reconstruction, and tuberculosis detection. It also explores techniques such as shape from focus, defocus, and image processing methods for accurate autofocusing in various imaging systems.
- Autofocusing
- Depth Estimation
- Microscopy
- Shape from Focus
- Defocus
- Image Processing
- Tuberculosis Detection
- Digital Imaging
- Machine Vision
- Neural Networks
- Research works
- 38k fractional, since 1950
- In the world top 10%
- 5.2k per year above
- Top-10% rate
- 13.8% share of its works in the world top 10%
- Growth, 2013–17 → 2018–22
- +13% the tick is no change
Which countries lead Image Processing Techniques and Applications research?
By volume, China and the United States publish the most (3.7k and 621 works in 2022–2025).
By volume, 2022–2025
- 1 China 3.7k works
- 2 United States 621 works
- 3 India 580 works
- 4 South Korea 251 works
- 5 Japan 237 works
- 6 Germany 175 works
- 7 United Kingdom 146 works
- 8 Taiwan 127 works
- 9 France 121 works
- 10 Russia 89 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 Processing Techniques and Applications research?
By volume in 2022–2025, Harbin Institute of Technology publishes the most Image Processing Techniques and Applications research, followed by Chinese Academy of Sciences and Beijing Institute of Technology.
By volume, 2022–2025
- 1 Harbin Institute of TechnologyChina 60 works
- 2 Chinese Academy of SciencesChina 60 works
- 3 Beijing Institute of TechnologyChina 57 works
- 4 Tsinghua UniversityChina 54 works
- 5 Nanjing University of Science and TechnologyChina 52 works
- 6 Zhejiang UniversityChina 51 works
- 7 University of Electronic Science and Technology of ChinaChina 49 works
- 8 National University of Defense TechnologyChina 47 works
- 9 Xidian UniversityChina 46 works
- 10 University of Chinese Academy of SciencesChina 45 works
Who are the leading researchers in Image Processing Techniques and Applications?
The most-cited researchers publishing on Image Processing Techniques and Applications include Andrew Zisserman, Pietro Perona and Wei Liu.
- 1 Andrew Zisserman United Kingdom 25k citations
- 2 Pietro Perona United States 11k citations
- 3 Wei Liu China 9.7k citations
- 4 Luc Van Gool Switzerland 8.5k citations
- 5 Alan Yuille United States 8.4k citations
- 6 Chen Change Loy Singapore 7.7k citations
- 7 Jiaya Jia Hong Kong 7.5k citations
- 8 Ming–Hsuan Yang United States 7.4k citations
- 9 Thomas S. Huang United States 7.4k citations
Ranked by citations received across their whole record, among researchers with at least three works on this topic.
Where is Image Processing Techniques and Applications research done?
The largest centres of Image Processing Techniques and Applications 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 Xi'an, Hsinchu and Shenzhen.
Largest cities, 2022–2025
Where it is the local speciality
- Xi'anCN · 247.1 works4.4×
- HsinchuTW · 25.3 works4.1×
- ShenzhenCN · 98.2 works4.1×
- HefeiCN · 103.1 works4.0×
Location quotient: how much more of its research is in Image Processing Techniques and Applications than the world average.
Where is the best place to study Image Processing Techniques and Applications?
Among universities, judged by research, Nanjing University of Science and Technology, Xidian University and Harbin Institute of Technology 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 | Nanjing University of Science and TechnologyChina | 61.5 | 20.4% | 8.9× | 52 | +38.2% |
| 2 | Xidian UniversityChina | 56.4 | 19.1% | 8.9× | 46 | -17.3% |
| 3 | Harbin Institute of TechnologyChina | 51.4 | 19.8% | 5.2× | 60 | +12.0% |
| 4 | Hong Kong Polytechnic UniversityHong Kong | 49.6 | 41.9% | 1.8× | 11 | +15.3% |
| 5 | University of Electronic Science and Technology of ChinaChina | 49.1 | 17.6% | 6.2× | 49 | -16.9% |
| 6 | National University of Defense TechnologyChina | 48.7 | 10.9% | 8.5× | 47 | -12.2% |
| 7 | Hong Kong University of Science and TechnologyHong Kong | 48.7 | 37.6% | 3.7× | 10 | -9.0% |
| 8 | Chinese University of Hong KongHong Kong | 48.4 | 37.5% | 2.5× | 12 | +13.6% |
| 9 | Chengdu University of Information TechnologyChina | 48.0 | 14.9% | 12.6× | 12 | +70.4% |
| 10 | Northwestern Polytechnical UniversityChina | 47.3 | 29.8% | 4.2× | 34 | -40.7% |
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 Processing Techniques and Applications research growing?
Output in 2018–2022 was 13% higher than in 2013–2017, peaking in 2024. The fastest-growing topics are Image Processing Techniques and Applications.
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.