Prof. Brian A. Wandell
at Stanford Univ
SPIE Involvement:
Author | Instructor
Publications (28)

Proceedings Article | 27 February 2015 Paper
Qiyuan Tian, Henryk Blasinski, Steven Lansel, Haomiao Jiang, Munenori Fukunishi, Joyce Farrell, Brian Wandell
Proceedings Volume 9404, 940403 (2015)
KEYWORDS: Cameras, Sensors, Image processing, Transform theory, Prototyping, Image sensors, Calibration, Device simulation, Data modeling, Video acceleration

Proceedings Article | 27 February 2015 Paper
Francois Germain, Iretiayo Akinola, Qiyuan Tian, Steven Lansel, Brian Wandell
Proceedings Volume 9404, 940404 (2015)
KEYWORDS: Sensors, Transform theory, Tungsten, Color reproduction, Image processing, Image sensors, Cameras, Device simulation, Data conversion, Denoising

Proceedings Article | 7 March 2014 Paper
Qiyuan Tian, Steven Lansel, Joyce Farrell, Brian Wandell
Proceedings Volume 9023, 90230K (2014)
KEYWORDS: Sensors, Image processing, Algorithm development, Optical filters, Image sensors, RGB color model, Image quality, Cameras, Signal to noise ratio, Chromium

Proceedings Article | 26 January 2010 Paper
Guillaume Leseur, Nicolas Meunier, Georgios Georgiadis, Lily Huang, Jeffrey DiCarlo, Brian Wandell, Peter Catrysse
Proceedings Volume 7536, 75360A (2010)
KEYWORDS: Sensors, CMYK color model, Sensing systems, Computing systems, Reflectivity, Printing, Computer simulations, Error analysis, CCD image sensors, Statistical analysis

Proceedings Article | 19 January 2010 Paper
Proceedings Volume 7537, 75370C (2010)
KEYWORDS: Sensors, Signal to noise ratio, Image sensors, Image quality, Spatial resolution, Modulation transfer functions, Imaging systems, Video, Visibility, Image processing

Showing 5 of 28 publications
Course Instructor
SC762: Device Simulation for Image Quality Evaluation
Customers judge the image quality of a digital camera by viewing the final rendered output. Achieving a high quality output depends on the multiple system components, including the optical system, imaging sensor, image processor and display device. Consequently, analyzing components singly, without reference to the characteristics of the other components, provides only a limited view of the system performance. An integrated simulation environment, that models the entire imaging pipeline, is a useful tool that improves understanding and guides design. This course will introduce computational models to simulate the scene, optics, sensor, processor, display, and human observer. Example simulations of calibrated devices and imaging algorithms will be used to clarify how specific system components influence the perceived quality of the final output.
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