World's Best Scientists 2026 revealed!
Award Badge
Rising Stars
2025

D-Index & Metrics

Rising Stars

D-Index
35
Citations
8800
World Ranking
820
National Ranking
270

Computer Science

D-Index
35
Citations
9953
World Ranking
11442
National Ranking
1419

Research.com Recognitions

  • 2025 - Research.com Rising Stars Award

Overview

Kede Ma is affiliated with the City University of Hong Kong in China and has contributed extensively to the field of computer science, with a primary focus on computer vision and pattern recognition. Their work spans fundamental and applied research in image and video quality assessment as well as advanced image processing methodologies.

The scientist's research predominantly covers the following topics:

  • Image and Video Quality Assessment
  • Advanced Image Fusion Techniques
  • Image Enhancement Techniques
  • Image and Signal Denoising Methods
  • Visual Attention and Saliency Detection
  • Advanced Image Processing Techniques
  • Advanced Vision and Imaging

Kede Ma has a strong publication record in major journals and repositories in the field. Frequent venues for their research include:

  • arXiv (Cornell University)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • IEEE Transactions on Image Processing
  • IEEE Transactions on Circuits and Systems for Video Technology
  • IEEE Transactions on Visualization and Computer Graphics

Recent papers with significant citation impact include:

  • "Image Quality Assessment: Unifying Structure and Texture Similarity," 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "Fast Multi-Scale Structural Patch Decomposition for Multi-Exposure Image Fusion," 2020, IEEE Transactions on Image Processing
  • "Continual Learning for Blind Image Quality Assessment," 2022, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "Perceptual Quality Assessment of Omnidirectional Images as Moving Camera Videos," 2021, IEEE Transactions on Visualization and Computer Graphics
  • "Analysis of Video Quality Datasets via Design of Minimalistic Video Quality Models," 2024, IEEE Transactions on Pattern Analysis and Machine Intelligence

Kede Ma collaborates frequently with colleagues known in the field, including:

  • Yuming Fang
  • Guangtao Zhai
  • Dingquan Li
  • Weixia Zhang
  • Xiaokang Yang

Their work integrates approaches from related subfields such as media technology, artificial intelligence, atomic and molecular physics and optics, and biomedical engineering, with the strongest focus on computer vision and pattern recognition.

Best Publications

  • Perceptual Quality Assessment for Multi-Exposure Image Fusion

    Kede Ma;Kai Zeng;Zhou Wang

  • Reversible Data Hiding in Encrypted Images by Reserving Room Before Encryption

    Kede Ma;Weiming Zhang;Xianfeng Zhao;Nenghai Yu

  • Blind Image Quality Assessment Using a Deep Bilinear Convolutional Neural Network

    Weixia Zhang;Kede Ma;Jia Yan;Dexiang Deng

  • Image Quality Assessment: Unifying Structure and Texture Similarity.

    Keyan Ding;Kede Ma;Shiqi Wang;Eero P. Simoncelli

  • Waterloo Exploration Database: New Challenges for Image Quality Assessment Models

    Kede Ma;Zhengfang Duanmu;Qingbo Wu;Zhou Wang

  • End-to-End Blind Image Quality Assessment Using Deep Neural Networks

    Kede Ma;Wentao Liu;Kai Zhang;Zhengfang Duanmu

  • Uncertainty-Aware Blind Image Quality Assessment in the Laboratory and Wild

    Weixia Zhang;Kede Ma;Guangtao Zhai;Xiaokang Yang

  • Reversibility improved data hiding in encrypted images

    Weiming Zhang;Kede Ma;Nenghai Yu

  • A Patch-Structure Representation Method for Quality Assessment of Contrast Changed Images

    Shiqi Wang;Kede Ma;Hojatollah Yeganeh;Zhou Wang

  • No-Reference Quality Assessment of Contrast-Distorted Images Based on Natural Scene Statistics

    Yuming Fang;Kede Ma;Zhou Wang;Weisi Lin

  • Robust Multi-Exposure Image Fusion: A Structural Patch Decomposition Approach

    Kede Ma;Hui Li;Hongwei Yong;Zhou Wang

  • dipIQ: Blind Image Quality Assessment by Learning-to-Rank Discriminable Image Pairs

    Kede Ma;Wentao Liu;Tongliang Liu;Zhou Wang

  • Perceptual Quality Assessment of Smartphone Photography

    Yuming Fang;Hanwei Zhu;Yan Zeng;Kede Ma

  • Unified Blind Quality Assessment of Compressed Natural, Graphic, and Screen Content Images

    Xiongkuo Min;Kede Ma;Ke Gu;Guangtao Zhai

  • Blind Image Quality Assessment via Vision-Language Correspondence: A Multitask Learning Perspective

    Unknown

  • A Quality-of-Experience Index for Streaming Video

    Zhengfang Duanmu;Kai Zeng;Kede Ma;Abdul Rehman

  • Multi-Exposure Image Fusion by Optimizing A Structural Similarity Index

    Kede Ma;Zhengfang Duanmu;Hojatollah Yeganeh;Zhou Wang

  • Deep Guided Learning for Fast Multi-Exposure Image Fusion

    Kede Ma;Zhengfang Duanmu;Hanwei Zhu;Yuming Fang

  • Fast Multi-Scale Structural Patch Decomposition for Multi-Exposure Image Fusion

    Hui Li;Kede Ma;Hongwei Yong;Lei Zhang

  • High Dynamic Range Image Compression by Optimizing Tone Mapped Image Quality Index

    Kede Ma;Hojatollah Yeganeh;Kai Zeng;Zhou Wang

  • Perceptual evaluation of single image dehazing algorithms

    Kede Ma;Wentao Liu;Zhou Wang

  • Multi-exposure image fusion: A patch-wise approach

    Kede Ma;Zhou Wang

  • Comparison of Full-Reference Image Quality Models for Optimization of Image Processing Systems

    Keyan Ding;Kede Ma;Shiqi Wang;Eero P. Simoncelli

Frequent Co-Authors

Zhou Wang
Zhou Wang University of Waterloo
Yuming Fang
Yuming Fang Jiangxi University of Finance and Economics
Shiqi Wang
Shiqi Wang City University of Hong Kong
Zhangyang Wang
Zhangyang Wang The University of Texas at Austin
Guangtao Zhai
Guangtao Zhai Shanghai Jiao Tong University
Xiaokang Yang
Xiaokang Yang Shanghai Jiao Tong University
Lei Zhang
Lei Zhang Hong Kong Polytechnic University
Dacheng Tao
Dacheng Tao Nanyang Technological University
Eero P. Simoncelli
Eero P. Simoncelli New York University
Tongliang Liu
Tongliang Liu University of Sydney

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring Computer Science in the USA unlocks numerous career opportunities and specialized study pathways. Many students choose flexible learning options by enrolling at one of the best online colleges. These programs offer nationally accredited degrees that let you study from anywhere without sacrificing quality.

For those interested in creative technology, accredited online video game design programs provide hands-on skills in digital arts, programming, and interactive storytelling. Security-focused learners might consider pursuing a cyber security degree, which prepares graduates to defend data and systems in a fast-growing industry.

If your interests lean towards engineering and project management, the bachelors construction management pathway blends technology with leadership in the expanding construction sector. All these online degrees offer diverse career options, industry-relevant curricula, and increased flexibility for balancing study with other commitments.

Best Scientists Citing Kede Ma

Trending Scientists