Professor Guoping Qiu has been researching neural networks and their applications in image processing since the 1990s. He spearheaded learning-based super-resolution techniques and developed early neural network solutions for image coding and compression artifact removal, well before deep learning became mainstream in these applications. He also introduced one of the earliest representation learning methods that leveraged unsupervised competitive neural networks for learning image features. He has been at the forefront of high dynamic range (HDR) imaging and pioneered tone-mapping methods that have fundamentally transformed how HDR content is processed and displayed. His group developed some of the best performing practical HDR tone mapping solutions that are widely cited by imaging industrial leaders including smartphone makers, camera manufacturers and imaging software companies. As Chief Scientist at Everimaging (www.everimaging.com), the company behind the multi-award-winning visual content creation software HDR Darkroom and Fotor with hundreds of millions global users, he is driving advancements in imaging technology research to solve real-world problems. With a distinguished career spanning academia and industry, Professor Qiu has contributed to fundamental research and real-world applications in imaging technology. Currently, he holds the position of Chair Professor of Visual Information Processing at the School of Computer Science, University of Nottingham, UK. Additionally, he is serving as the Vice Provost for Education and Student Experience at the University of Nottingham Ningbo China (UNNC), overseeing the education and student experience of a diverse academic community of over 11,000 students and faculty from over 70 countries and regions. UNNC delivers all its teaching in English and offers undergraduate, Master's, and PhD programs across business, humanities, social sciences, and science and engineering, awarding degrees from the University of Nottingham.

 

Speech Title: High Dynamic Range – The Last Frontier of Digital Imaging
Abstract:
Many years of research and development plus billions of dollars investment in technology have made digital photography device ubiquitous and very sophisticated. Despite huge progress, there are still the occasions, for example when taking a photo of an evening party at a restaurant, where the image quality will still come out poorly. Either the dark shadows are too dark such that no details are visible, or the light areas are so bright such that they are completely saturated, and no details are visible. Even after turning on the high dynamic range (HDR) function in your camera which is now a feature in every smartphone, or adjusting the various control buttons, the situations will not improve much. And yet the photographer on the scene can clearly see every detail both in the dark and in the bright regions. The question is, why? In this talk I will show that this difficulty is caused by the high dynamic range of the light intensities of the scene, and we call this the HDR problem. I will show from first principle that HDR is the cause of many difficulties in digital imaging (photography) and correct some of the misconceptions in many recent literatures on image processing problems such as low-light (or dark) image enhancement, especially those so-called end-to-end blackbox solutions based on deep learning. I will demonstrate both theoretically and in practice that HDR is the last technical obstacle, the last frontier, of digital imaging.