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Lingnan’s Highly Cited Researcher drives real-world transformations
“As computer scientists today, we have all these tools available. How are we going to make use of them to create a better life for our society or for the next generation?” That is the question posed by Prof Sam Kwong Tak-wu, an eminent scientist who joined Lingnan University as Associate VicePresident (Strategic Research) and Chair Professor of Computational Intelligence in September 2023.
Prof Kwong has a notable level of expertise in fields ranging from computer science, engineering and telecommunications to automation and control systems, and imaging science and photographic technology. And he has already made history at Lingnan by becoming the first faculty member to be named as a Highly Cited Researcher.
This prestigious form of recognition is accorded by Clarivate and given to those whose work ranks in the top 1 per cent by citations for their fields and publication year over the past decade. Scholars from 67 countries and regions worldwide were named as Highly Cited Researchers in 2023 and, earlier in the year, Prof Kwong was also included on the Stanford University list of the World’s Top 2% Scientists.
“I am deeply honoured to receive this recognition for my research, which I believe reflects the outstanding research and influence of Lingnan University,” he said. “This would not have been possible without the support of my colleagues and students, and I am grateful for their contribution to our research.”
Pioneering genetic algorithms
Prof Kwong’s pioneering research began some three decades ago with work on genetic algorithms, a farreaching specialism of great moment, as evidenced by the two authoritative best-selling books on the subject prominently displayed on his office bookshelf.
“When genetic algorithms were in their infancy, I think we were one of the first to use them for other problems, like speech recognition and many other practical tests,” he explained. “Over time, it became apparent that genetic algorithms were not only effective for numerical issues, but also for practical industrial challenges. The evolutionary computational algorithms mimic the concept of survival of the fittest. That is a very interesting thing. It relies on two operators: crossover and mutation, and is basically the same as what humans do in our evolution.”
Prof Kwong traces the history of artificial intelligence back to the Dartmouth Conference in the 1950s when the term was first coined. Networks have been around since the 1980s. And nowadays, we have access to very powerful computers that have facilitated the evolution of computational algorithms and led to the emergence of new networks, deep learning, and AI.
"We had all these ideas in the early 1980s and 1990s, but it is only today that we are seeing something that is truly like Star Wars," he said.
Enabling cutting-edge technologies
Driven by a passion for research, Prof Kwong has made substantial contributions to advanced evolutionary computation theory. His work has also demonstrated the feasibility of interdisciplinary applications, starting with video encoding and, more recently, culminating in work on lowlight enhancement and underwater image systems. In this area, he has improved the quality of images captured in exacting environments, and developed several algorithms for strengthening low-light images, which are often noisy and lack detail. His research has focused on developing techniques that enhance image quality while preserving important features such as edges and texture.
These practical solutions and various tools, developed in collaboration with industry partners, have made it possible to incorporate cutting-edge technologies in multimedia systems, and led to other industrial applications, which all make for a better user experience when viewing videos.
"As a pioneer in the field of computational intelligence, I am committed to continuing my research and making further contributions to academia and the wider society,” he said. “I am excited to be part of this important work.”
Bright future
In addition, Prof Kwong feels that Lingnan University is starting a new chapter under the leadership of President S. Joe Qin and, in line with the President's vision, can become a world-class, research-based liberal arts university.
“I look forward to working together to make the university better,” he said. “And I am excited to see how I can leverage my knowledge to help Lingnan reach new heights. I think because of its individuality, Lingnan can play an important role not only in Hong Kong and the Greater Bay Area, but also globally. Our size allows us to excel, just like some of the prestigious Ivy League universities in the US that are not so big. Given these conditions, I am optimistic that Lingnan will do well over the next ten years.”
As a pioneer in the field of computational intelligence, I am committed to continuing my research and making further contributions to academia and the wider society. — Prof Sam Kwong
Groundbreaking research
With a remarkable track record of scientific breakthroughs and contributions to society, Prof Kwong’s influence is far-reaching. In addition to his work on evolutionary computation, low-light enhancement and underwater image systems, other notable distinctions include:
• Science and Technology Award of the CSIG
Prof Kwong's research project "Cross-modality interaction and remote perception theory and method for salient attribute mining" won the Second Prize of the Natural Science Award of the Science and Technology Award of the China Society of Image and Graphics (CSIG) in 2023.
• Major Ministry of Education award
Prof Kwong and his team's project, titled "High-efficiency Computing Theory and Method for Video Coding", received the Second Class Awards in the Natural Science category at the Higher Education Outstanding Scientific Research Output Awards (Science and Technology) in 2020, which is a major Ministry of Education award.
After conducting extensive research for over a decade, Prof Kwong and the team have contributed to the ultra-high-definition video industry by developing new theories and methods for enhancing the algorithm efficiency for video coding in three key respects: optimal mode decision, sparse transformation quantisation, and motion estimation optimisation. Published in journals included in the Science Citation Index, the team’s 59 academic papers have been cited positively by fellows of academies of science and engineering around the world, as well as over 50 IEEE and Association for Computing Machinery fellows.
• Influential papers
Prof Kwong has published extensively in the field of low-light intensification and underwater image systems, including numerous papers in top-tier IEEE journals and conferences such as CVPR, ECCV, and ICCV.
His paper "Zero-reference deep curve estimation for low-light image enhancement", published in CVPR 2020 has been recognised as among the most influential in the field and frequently quoted, with close to 1,000 citations according to Google Scholar. His research has had a powerful effect on various real-world applications, improving the quality and usefulness of images captured in low-light and underwater environments.
• Benchmark
His underwater image work “An underwater image enhancement benchmark dataset and beyond”, published in IEEE Transactions on Image Processing in 2020, is groundbreaking, as he has developed an archetype dataset that includes diverse underwater scenes and difficult degradations, which has become a de facto benchmark in the underwater image processing community. His baseline model trained using this dataset, combining deep learning with image processing techniques, has achieved better performance than commercial software such as Dive+. This paper has received over 900 citations in a short time, demonstrating its significance and importance in the field.
• Significant impact on different applications
Prof Kwong and his team have developed an efficient and robust method called MLLE to enhance underwater images, which often suffer from colour deviations and low visibility due to wavelength-dependent light absorption and scattering. The MLLE method employs a minimum colour loss principle and a maximum attenuation map-guided fusion strategy to locally adjust the colour and details of the input image. Additionally, integral and squared integral maps are used to compute the mean and variance of local image blocks, in order to adaptively adjust the contrast of the input image. The enhanced images produced by MLLE exhibit vivid colour, improved contrast, and enhanced details.
This groundbreaking work was published in IEEE Transactions on Image Processing in June 2022 under the title "Underwater Image Enhancement via Minimal Color Loss and Locally Adaptive Contrast Enhancement". Prof Kwong's research has also had a profound impact in numerous fields, including marine biology, and oceanography.
Prof Sam Kwong Tak-wu
• IEEE Chester W. Sall Memorial Awards 2024 Best Paper Award
• Fellow of the Hong Kong Academy of Engineering Sciences
• First Lingnan scholar elected as Fellow of the National Academy of Inventors 2023
• Second Prize of the Natural Science Award of the 2023 Science and Technology Award of the China Society of Image and Graphics
• First Lingnan faculty member to be named Highly Cited Researcher 2023
• World’s Top 2% Scientists by Stanford University 2023
• Speaker at the Distinguished Scholars Seminar Series 2023
