The exponential growth in the volume and complexity of digital image data, particularly in fields such as medical diagnostics, satellite remote sensing, and artificial intelligence, presents significant challenges for classical computation. Traditional image processing techniques are increasingly constrained by the computational limits of classical hardware. Quantum Computing (QC) emerges as a transformative paradigm, offering a fundamentally new approach to computation by leveraging the principles of quantum mechanics, including superposition and entanglement.
This keynote explores the potential of quantum computing to revolutionize image processing applications. We review the foundational concepts of Quantum Image Processing. This keynote will enlighten the development of novel quantum algorithms that promise exponential speedups in critical tasks such as edge detection, image segmentation, filtering, and feature extraction. Particular attention is given to the potential impact on medical imaging, where quantum algorithms could drastically reduce image reconstruction times for MRI and CT scans, enhance diagnostic accuracy through superior pattern recognition, and reduce patient exposure to radiation. While the field is still in its early stages, quantum image processing holds significant potential to solve computationally intractable problems, enabling real-time analysis of high-dimensional image data and unlocking new capabilities in computer vision and data science.
Mohd Shafry Mohd Rahim is a Professor of Image Processing at the Faculty of Computing, University Teknologi Malaysia (UTM), Malaysia. He also serves as Research Fellow of Media and Game Innovation of Excellence (MaGICX), Institute of Human-Centred Engineering (iHuMeN), University Teknologi Malaysia and leading Image Processing and Application Research Initiatives. His passion is to explore new invention on processing various type images in the emerging application based on the revolution of technology for prospering lives. His research interests include image enhancement, feature extraction, segmentation, recognition, detection and classification; deep learning, computer graphics, computer vision and digital media. He currently holds the position of Vice-Chancellor of UTM.