Color and the Camera Imaging Pipeline
Instructor: Michael S. Brown, York University
Level: Intermediate
Duration: 2 hours plus 15 minute break. After the class, adjourn to Zoom to join the instructor and other students in a discussion of the class.
Course Time:
    New York: Wednesday 4 November, 18:30-20:45
    Paris: Thursday 5 November, 00:30-02:45
    Tokyo: Thursday 5 November, 08:30-10:45

Benefits:
Attendees will be able to:

• Background on color theory and color spaces related to camera imaging.
• Overview the common steps applied by the camera's image signal processor (ISP) that are used to process the raw sensor image to its final photo-finished output.
• Understand the contribution of each of the ISP steps to the final appearance of the image.
• Discuss recent multi-frame processing approaches for HDR and night mode.

 Intended audience: engineer/scientist working with images for a range of applications from photographer to scientific imaging.

Course Description:
Consumer cameras apply a number of processing steps to convert the incoming light falling on the camera's sensor to the final output that is saved when we click to capture a photo. This short course provides a thorough overview of the processing routines commonly applied by the camera's image signal processing (ISP) hardware to process capture images. The course is organized into two parts. The first part provides the necessary preliminaries on perceptual colour spaces and human colour vision as they pertain to the camera processing pipeline.

The second part of the course describes the ISP's processing routines such as linearization, demosaicing, denoising, white-balance, sensor characteristic adaptation, colour manipulation for photo-finishing, display-referred colour space conversion, image resizing and super-resolution, and final compression. The latter part also cover multi-frame methods that fuse multiple captured images for HDR and night-mode.

Michael S. Brown is a professor and Canada Research Chair in Computer Vision at York University in Toronto. His research interests include computer vision, image processing and computer graphics. Brown has served as an area chair multiple times for CVPR, ICCV, ECCV, ACCV, BMVC, and as an associate editor for the IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) and the International Journal of Computer Vision (IJCV).   He has served as program chair for WACV 2011/17/19 and 3DV 2015 and as general chair for ACCV 2014 and CVPR 2018.  Brown is currently on leave from York University as a senior research director for the Samsung AI Center in Toronto, Canada.

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