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Registration Opens late August
Last Day to Register
28 September
Short Courses and Tutorial
29 September
Technical Program
30 Sept - 1 Oct


Updated 4 August 2020
Subject to change

** Times listed are BST (London) time **

Tuesday 29 September 2020

Comprehensive Colour Appearance Modelling (CCAM)

separate registration fee required

Course Number: LIMSC01
Level: Intermediate
Prerequisites: Understanding of basic colorimetry
Instructor: Ming Ronnier Luo, Zhejiang University (China)

Benefits: This course enables the attendee to:

  • Understand understand the fundamentals of color appearance mechanism of color signal processing, and of viewing field definition, viewing condition parameters, perceptual correlates, and visual phenomena together with its application on cross media and viewing conditions color reproduction.
  • Introduce the CIE CAMs including CIECAM97s, CIECAM02, CIECAM16, and its extension to uniform color space, CAM02-UCS, CAM16-UCS, including new models such as ZCAM from Jzazbz UCS.
  • Develop new functions for predicting color appearance against colored background (color contrast effect), of new 2D color appearance correlates (Whiteness, Blackness, Vividness, Depth), and of varying field of view from 2° - 50°
  • Extend CAMs for HDR and WCG applications, recent studies on color difference evaluation, color appearance scaling, and hue linearity assessment.
  • Extend CAMs for unrelated colors from mesopic to photopic region.

Course Description
Color appearance models have been widely applied to achieve cross-media color reproduction in the color imaging industry. CIE standardized its first model CIECAM97s in 1997, then CIECAM02 in 2002, and the new CIECAM16, to be the new recommendation in the near future. This course starts with the fundamental components, the perceptual correlates, and visual phenomena of CAMs. More attention is be paid to recent studies intended to extend CAM’s functions including color contrast, 2D color appearance scales, and unrelated colors. For the highly desired HDR and WCG applications, new experimental results were obtained to extend CAMs to estimate color difference, color appearance, and hue linearity.

Intended Audience: Scientists, engineers, and students who consider cross-media and cross-viewing conditions color reproduction in the imaging industries, and anyone who wants to know more about the set up of experimental conditions to perform HDR and WCG color appearance research.

Ming Ronnier Luo is a professor at the College of Optical Science and Engineering at Zhejiang University (China). He is also a visiting professor of Colour Science and Imaging at University of Leeds (UK). He received his PhD (1986) from the University of Bradford, UK in the field of color science. His main research areas include color science, imaging science, and LED illumination. He has published over 650 scientific papers. He is a Fellow of IS&T and the Society of Dyers and Colourists (SDC). He is past-vice-president and past-director of Division 1 (Colour and Vision) of International Commission of Illumination (CIE). In 2017 he received the Judd Award from AIC and in 2020 the Newton Award from the Colour Group of Great Britain for his research achievements.

Chromatic Adaptation and Its Application in Imaging Systems

separate registration fee required

Course Number: LIMSC02
Understanding of basic colorimetry
Minchen (Tommy) Wei, The Hong Kong Polytechnic University (Hong Kong)

Benefits: This course enables the attendee to:

  • Understand chromatic adaptation mechanism in the human visual system.
  • Compare different chromatic adaptation transforms (CATs).
  • Understand the latest research on chromatic adaptation.
  • Apply chromatic adaptation in imaging systems.

Course Description
Chromatic adaptation is an important mechanism in the human visual system. It significantly affects the color appearance of stimuli under different viewing conditions, and it attracts great attention in the color and imaging industries. With the development of LED lighting and imaging systems, chromatic adaptation needs to be further investigated. This course provides an overview of chromatic adaptation and chromatic adaptation transforms; it also discusses some of the latest research on chromatic adaptation and its application in imaging systems.

Intended Audience: Scientists, engineers, and students using color appearance models and chromatic adaptation transforms for research, product development, and evaluations.

Minchen (Tommy) Wei is an associate professor at The Hong Kong Polytechnic University. He received his bachelor’s degree from Fudan University (2009) and his MS (2011) and PhD (2015) in Architectural Engineering from Penn State University. His research mainly focuses on color science and its application in illumination and imaging systems.


Understanding Color and Your Camera Tutorial
(updated August 2020)

complementary with conference registration
presented by Prof. Michael Brown, York University (Canada)

This tutorial provides a background on color and its relationship to the in-camera processing pipeline. The tutorial is organized into two parts. The first part provides a background on color theory and color representations, namely the CIE 1931 XYZ color space and its derivatives commonly found on consumer devices. The second part provides a high-level discussion on routines applied onboard cameras to convert the low-level sensor raw-RGB responses to their final standard RGB (sRGB) colors. The tutorial ends with various misconceptions about color and camera images made in many research areas such as image processing and computer vision. The tutorial takes place on 29 September and is included in the registration fee.

Part 1 - Background on Color
  • Radiometric vs. colorimetric measurements
  • CIE XYZ matching functions and relationship to colorimetry
  • Color Constancy and its relationship to color temperatures
  • Standard color spaces for consumer cameras
Part 2 - Camera processing pipeline
  • RAW/Bayer processing
  • Sensor characterization
  • Image processing engine
  • JPEG and output color spaces
Part 3 - Misconceptions
  • Common misconceptions about camera images and color made in the image processing and computer vision literature



Updated 4 August 2020
Subject to change

** Times listed are London, UK time **

Wednesday 30 September 2020

9:00 Conference Welcome

Session I: Color Science and Applications
Focal Talk: An Overview of the Recent Developments on Colour Science, Ming Ronnier Luo, Zhejiang University (China)

9:45 Investigation of Spatial Chromatic Contrast around 5 Colour Centres, Qiang Xu and Ming Ronnier Luo, Zhejiang University (China)

10:05 Assessing Skin Colour Heterogeneity under Various Light Sources, Ruili He, Kaida Xiao, Michael Pointer, and Stephen Westland, University of Leeds (UK)

10:25 Preferred Skin Color Center on Mobile Displays under Different Ambient Lightings Contrast Sensitivity Functions for HDR Displays, Minjung Kim1, Maliha Ashraf2, Maria Perez-Ortiz3, Jasna Martinovic4, Sophie Wuerger2, and Rafal Mantiuk1; 1University of Cambridge, 2University of Liverpool, 3University College London, and 4University of Aberdeen (UK)

10:45 2-Minute Interactive (Poster) Previews, Group A

  • Texture Stationarity Evaluation With Local Wavelet SpectrumMichele Conni1,2 and Hilda Deborah21Barbieri Electronic (Italy) and 2Norges Teknisk-Naturvitenskapelige Universitet (Norway)
  • Modelling and Modification of Simultaneous Lightness Contrast Effect Using Albers’ PatternYuechen Zhu and Ming Ronnier Luo, Zhejiang University (China)
  • Parameters Optimization of the Structural Similarity Index, Illya Bakurov1, Marco Buzzelli2, Mauro Castelli1, Raimondo Schettini2, and Leonardo Vanneschi11Universidade Nova de Lisboa (Portugal) and 2University of Milano – Bicocca (Italy)
  • Color Image Evaluation of Congenital Red-Green Color Deficient and Normal Color Vision ObserversMiyoshi Ayama, Minoru Ohkoba, Kahori Tanaka, and Tomoharu Ishikawa, Utsunomiya University (Japan)

11:00 Coffee Break / Interactive (Poster) Papers, Group A

Session II: Perception
Focal Talk: Surface Color under Environmental Illumination, Hannah Smithson, Oxford University (UK)

12:10 The Persistent Influence of Viewing Environment Illumination Color on Displayed Image Appearance, Trevor Canham and Marcelo Bertalmío, Universitat Pompeu Fabra (Spain)

12:30 Contrast Sensitivity Functions for HDR Displays, Minjung Kim1, Maliha Ashraf2, Maria Perez-Ortiz3, Jasna Martinovic4, Sophie Wuerger2, and Rafal Mantiuk1; 1University of Cambridge, 2University of Liverpool, 3University College London, and 4University of Aberdeen (UK)

12:50  Fast Chromatic Adaptation Transform Utilizing Wpt based Spectral Reconstruction, Maxim Derhak and Lin Luo, Onyx Graphics Inc., (US), and Phillip Green, Norwegian University of Science and Technology (Norway)

13:10 2-Minute Interactive (Poster) Previews, Group B

  • Physics-based Modeling of a Light Booth to Improve Color Accuracy of 3D RenderingKhalil Huraibat and Esther Perales , Universidad de Alicante (Spain); Eric Kirchner and Ivo van der Lans, AkzoNobel (the Netherlands); and Alejandro Ferrero and Joaquín Campos, Instituto de Óptica (Spain)
  • Linear Histogram Adjustment for Image EnhancementJake McVey, University of East Anglia (UK)
  • Evaluation of the Human Visual System in Cosmetics Foundation Colour SelectionAltynay Kadyrova and Majid Ansari-Asl, Norwegian University of Science and Technology (Norway), and Eva M. Valero Benito, University of Granada (Spain)
  • Solar Limb Darkening Color Imaging of The Sun With The Extreme Brightness Capability CAOS CameraNabeel A. Riza, Mohsin A. Mazhar, and Nazim Ashraf, University College Cork (Ireland)

13:20 Lunch Break / Interactive (Poster) Papers, Group B

Session III: Visibility
Focal Talk: Imaging the Visible beyond RGB, Jon Hardeberg, Norwegian University of Science and Technology (Norway)

14:30 Single Image Dehazing by Predicting Atmospheric Scattering Parameters, Simone Bianco, Luigi Celona, Flavio Piccoli, and Raimondo Schettini, University of Milano – Bicocca (Italy)

14:50 CNN-based Rain Reduction in Street View Images, Simone Zini, Simone Bianco, and Raimondo Schettini, University of Milano – Bicocca (Italy)

15:10 CNN-based Rain Reduction in Street View ImagesIllumination-invariant Image from 4-channel Images: The Effect of Near-infrared Data in Shadow Removal, Sorour Mohajerani, Mark Drew, and Parvaneh Saeedi, Simon Fraser University (Canada)

15:30-13:30  Stretch Break

15:45 Keynote:  Surface Color Perception in Realistic Scenes: Previews of a Future Color Science, Laurence Maloney, New York University (US)
Research in the past two decades has shown that surface color perception in natural scenes is profoundly connected with perception of the spatial layout of the scene. This talk describes the spatial information human observers get from scenes that affects their perception of surface color and material and what it would mean to match human performance.


Thursday 1 October 2020

9:00 Conference Welcome

Session IV: Image Reproduction
9:15 Focal Talk: Graphical 3D Printing: Challenges, Solutions, and Applications, Philipp Urban, Fraunhofer Institute for Computer Graphics Research IGD (Germany)

9:45 A Practical Approach on Non-regular Sampling and Universal Demosaicing of Raw Image Sensor Data, Philipp Backes and Jan Fröhlich, Stuttgart Media University (HDM) (Germany)

10:05 Designing a Physically-feasible Colour Filter to Make a Camera More Colorimetric, Yuteng Zhu, University of East Anglia (UK)

10:25 A Correspondence-free Color Chart Design for Color Calibration, Hakki Karaimer, Ecole Polytechnique Fédérale de Lausanne (EPFL) (Switzerland) and Rang Nguyen, Ho Chi Minh City University of Technology (Vietnam)

10:45 2-Minute Interactive (Poster) Previews, Group C

  • Physical Patient Simulators for Surgical Training: A ReviewMarine Shao, Carinna Parraman, and David Huson, University of the West of England, Bristol (UK)
  • Colour Key-Point DetectionHermine Chatoux and Noel Richard, XLIM Laboratory (France)
  • Opponent Center-Surround Contrast: Colour to Grey ConversionAli Alsam, Norwegian University of Science and Technology (Norway)
  • Potential and Challenges of Spectral Imaging for Documentation and Analysis of Stained-Glass WindowsAgnese Babini1, Sony George1, Tiziana Lombardo2, and Jon Yngve Hardeberg11Norwegian University of Science and Technology  (Norway) and 2Swiss National Museum (Switzerland)
  • Implementing Directional Reflectance in a Colour Managed WorkflowTanzima Habib, Aditya Sole, and Phil Green, Norwegian University of Science and Technology (Norway)

11:00 Coffee Break / Interactive (Poster) Papers, Group C

Session V: Computer Vision

11:50 Focal Talk: CNN-based Image Quality Assessment, Raimondo Schettini, University of Milano-Bicocca (Italy)

12:20 Deep Optimal Filter Responses for Multi-spectral Imaging, Tarek Stiebel and Dorit Merhof, RWTH Aachen University (Germany)

12:40 Light Direction and Color Estimation from Single Image with Deep Regression, Hassan Ahmed Sial, Ramon Baldrich, and Maria Vanrell, Universitat Autònoma de Barcelona (Spain), and Dimitris Samaras, Stony Brook University (US)

13:00 Colour Fidelity in Spectral Reconstruction from RGB Images, Yi-Tun Lin, University of East Anglia (UK)

13:20 2-Minute Work-in-Progress Poster Previews

  • Spectroradiometric Measurements of the Reflectance of the Human Sclera in Vivo, Miranda Nixon, Felix Outlaw, Lindsay W. MacDonald, and Terence S. Leung, University College London (UK)
    A Color Preserving Chroma Processing Technique for HDR Video Compression, Maryam Azimi, Cambridge University (UK)
  • Thin Film Structures for Colour-Shift Effects, Riley Shurvinton, Antonin Moreau, Fabien Lemarchand,  and Julien Lumeau, Institut Fresnel (France)
  • Online versus Offline Colour Naming Experiments, Dimitris Mylonas, Lewis D Griffin, and Andrew Stockman, University College London (UK)
  • Discrimination of Temporal Illumination Changes, Ruben Pastilha, Gaurav Gupta, Naomi Gross, and Anya Hurlbert, Newcastle University (UK)
  • Adversarially Constrained Camera Model Anonymisation, Jerone Andrews, Yidan Zhang, and Lewis Griffin, University College London (UK)
  • Novel Metrics for the Calibration and Characterization of a Multi-primary High Dynamic Range Display, Allie Hexley,1 Manuel Spitschan,1 Rafal Mantiuk,2 and Hannah Smithson1; 1University of Oxford and 2University of Cambridge (UK)
  • Development of a Large Gamut Equalization Experiment Setup, Emilie Robert,1 Magali Estribeau,1 Rémi Barbier,1 Greggory Swiathy,2 2DGA TA; Justin Plantier,3 3IRBA; and Pierre Magnan1; 1ISAE SUPAERO, 2DGA TA, and 3IRBA (France)
  • Spatial and Angular Variations of Colour Rendition due to Inter-reflections, Cehao Yu and Sylvia Pont, Delft University of Technology (Netherlands)

13:40 Lunch Break / Work-in-Progress Posters

  Keynote: Designing Cameras to Detect the “Invisible”: Towards Domain-Specific Computational Imaging, Felix Heide, Princeton University (US)

Imaging has become an essential part of how we communicate with each other, how autonomous agents sense the world and act independently, and how we research chemical reactions and biological processes. Today's imaging and computer vision systems, however, often fail in the “edge cases'', for example in low light, fog, snow, or highly dynamic scenes. These edge cases are a result of ambiguity present in the scene or signal itself, and ambiguity introduced by imperfect capture systems. This talk presents several examples of computational imaging methods that resolve this ambiguity by jointly designing sensing and computation for domain-specific applications. Instead of relying on intermediate image representations, which are often optimized for human viewing, these cameras are designed end-to-end for a domain-specific task. In particular, the talk shows how to co-design automotive HDR ISPs, detection, and tracking (beating Tesla's latest OTA Model S Autopilot); how to optimize thin freeform lenses for wide field of view applications; and how to extract accurate dense depth from three gated images (beating scanning lidar, such as Velodyne's HDL64). It ends by presenting computational imaging systems that extract domain-specific information from faint measurement noise using domain-specific priors, allowing us to use conventional intensity cameras or conventional Doppler radar to image "hidden'' objects outside the direct line of sight at long ranges.

15:20  Best Paper Award Presentation and Closing Remarks

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