We live in a visual world. The perceived quality of images is of crucial importance in industrial, medical, and entertainment application environments. Developments in camera sensors, image processing, 3D imaging, display technology, and digital printing are enabling new or enhanced possibilities for creating and conveying visual content that informs or entertains. Wireless networks and mobile devices expand the ways to share imagery and autonomous vehicles bring image processing into new aspects of society.
The power of imaging rests directly on the visual quality of the images and the performance of the systems that produce them. As the images are generally intended to be viewed by humans, a deep understanding of human visual perception is key to the effective assessment of image quality.
This conference brings together engineers and scientists from industry and academia who strive to understand what makes a high-quality image, and how to specify the requirements and assess the performance of modern imaging systems. It focuses on objective and subjective methods for evaluating the perceptual quality of images, and includes applications throughout the imaging chain from image capture, through processing, to output, printed or displayed, video or still, 2D or 3D, virtual, mixed or augmented reality, LDR or HDR.
The conference on Image Quality and System Performance will celebrate its 20th Anniversary at EI 2023. To commemorate the event, a dedicated session will be organized.
2024 Conference Topics
- Image quality attributes, characterization, and metrics
- Perceptual image quality understanding
- Test image databases with perceptual reference data
- Image preference, saliency, scene dependency
- Image quality survey design (print, web-based, mobile)
- Machine learning visual quality methods (e.g., CNN)
- No-reference and multi-modal (audio and video) metrics
- Quality of experience for immersive media technologies (VR, AR, 360° video)
- Task-oriented image quality evaluation (e.g., medical, imaging, automotive vision, remote sensing)
- Imaging system simulation and modeling
- Camera ISP tuning and quality trade-offs
- Autonomous vehicle vision system performance
- Image noise analysis and color error propagation
- Gamut size, color rendering, ICC profile evaluation
- Methods for competitive bench marking, quality assurance
- Multi-media and cross-media system evaluations
Standards for image quality and system performance
- Standards for image and video quality
- Mobile, automotive, and video imaging performance
- Measurement of print and display microstructure (edges, color, resolution, distortion, etc.)
2024 Special Sessions
Visual Quality Across Displays and Viewing Conditions
We are interested in methods intended to measure/model/improve perceived image quality for electronic displays, including HDR, OLED and VR/AR displays. We are particularly interested in the methods that involve models of the visual system and those that account for the viewing conditions (ambient light and viewing distance). This special session is co-organized with the Human Vision and Electronic Imaging (HVEI) Conference. We welcome submissions in the following areas:
- Display as a factor of the quality of experience
- The effect of display resolution, size, and viewing distance on the visibility of image/video distortions or overall image quality
- The effect of ambient light and display brightness on the visibility of image/video distortions or overall image quality
- Quantifying the quality degradation due to display distortions
- Standards related to perceived display quality
- Perception-motivated display algorithms
- Display-adaptive video/image processing
- Visual models and metrics for quantifying display quality
- Perceptual measurements of display quality
- Human visual perception in display design
- Human perception and new display technologies
Best Paper Award*
*Note that competitors for the award must submit their final full proceedings paper for consideration after abstract acceptance.
Ling-Qi Zhang¹'², Minjung Kim¹, James Hillis¹, and Trisha Lian¹ ¹Meta Reality Labs and ²University of Pennsylvania (United States) for their work titled "Towards an image-computable visual text quality metric using deep neural networks."
Abderrezzaq Sendjasni, Mohamed Chaker Larabi, and Faouzi Alaya Cheikh (Université de Poitiers (France) and Norwegian University of Science and Technology (Norway)) for their work on "Patch-based CNN model for 360 image quality assessment with adaptive pooling strategies."
Oliver van Zwanenberg, Sophie Triantaphillidou, Robin Jenkin, and Alexandra Psarrou (University of Westminster) for their work on "Camera system performance derived from natural scenes."
Uwe Artmann (Image Engineering GmbH & Co. KG) for his work titled, "Quantify aliasing – A new approach to make resolution measurement more robust."
||Best Student Paper
Helard Becerra (University of Brasilia) for his work titled "Analyzing the influence of cross-modal IP-based degradations on the perceived audio-visual quality."
Clement Viard (DxOMark Image Labs) for his work on "Quantitative measurement of contrast, texture, color, and noise for digital photography of high dynamic range scenes."
||Best Student Paper
Edward Fry (University of Westminster) for his work on "Bridging the gap between imaging performance and image quality measures."
Seyed Ali Amirshahi, Marius Pedersen, and Stella X. Yuq (University of California, Berkeley and Norwegian University of Science and Technology) for their work titled, "Image quality assessment by comparing CNN features between images."
||Best Student Paper
Pedro Garcia Freitas and Welington Akamine (University of Brasilia) for their work titled, "Blind image quality assessment using multiscale local binary patterns."
Iana Iatsun, Chaker Larabi, Christine Fernandez Maloigne (Université de Poitiers) for their work on "Using binocular and monocular properties for the construction of a quality assessment metric for stereoscopic images."
||Best Student Paper
Praveen Cyriac (Universitat Pompeu Fabra) for his work on "Optimized tone curve for in-camera image processing."
Mohamed-Chaker Larabi, University of Poitiers (France)
Jonathan Phillips, Imatest, LLC (United States)
Nicolas Bonnier, Apple Inc. (US)
Alan Bovik, University of Texas at Austin (US)
Peter Burns, Burns Digital Imaging (US)
Anustup Choudhury, Dolby Laboratories (US)
Brian Cooper, Lexmark International, Inc. (US)
Luke Cui, Amazon (US)
Mylène C.Q. Farias, Texas State University (US)
Susan Farnand, Rochester Institute of Technology (US)
Frans Gaykema, Canon Production Printing Netherlands (the Netherlands)
Jukka Häkkinen, University of Helsinki (Finland)
Dirk Hertel, E Ink Corporation (US)
Robin Jenkin, NVIDIA Corporation (US)
Elaine Jin, Rivian Automotive, Inc. (US)
Göte Nyman, University of Helsinki (Finland)
Stuart Perry, University of Technology Sydney (Australia)
Sophie Triantaphillidou, University of Westminster (UK)