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

PROCEEDINGS ARTICLE | February 27, 2015
Proc. SPIE. 9404, Digital Photography XI
KEYWORDS: Video acceleration, Data modeling, Cameras, Sensors, Calibration, Image processing, Transform theory, Image sensors, Prototyping, Device simulation

PROCEEDINGS ARTICLE | February 27, 2015
Proc. SPIE. 9404, Digital Photography XI
KEYWORDS: Cameras, Sensors, Image processing, Denoising, Tungsten, Transform theory, Image sensors, Data conversion, Color reproduction, Device simulation

PROCEEDINGS ARTICLE | March 7, 2014
Proc. SPIE. 9023, Digital Photography X
KEYWORDS: Signal to noise ratio, Optical filters, Cameras, Sensors, Image processing, Chromium, Image quality, Image sensors, Algorithm development, RGB color model

PROCEEDINGS ARTICLE | January 26, 2010
Proc. SPIE. 7536, Sensors, Cameras, and Systems for Industrial/Scientific Applications XI
KEYWORDS: Statistical analysis, Sensors, Error analysis, Reflectivity, Computing systems, Computer simulations, Printing, Sensing systems, CCD image sensors, CMYK color model

PROCEEDINGS ARTICLE | January 19, 2010
Proc. SPIE. 7537, Digital Photography VI
KEYWORDS: Signal to noise ratio, Imaging systems, Sensors, Image processing, Video, Image quality, Image sensors, Modulation transfer functions, Spatial resolution, Visibility

PROCEEDINGS ARTICLE | February 18, 2009
Proc. SPIE. 7246, Computational Imaging VII
KEYWORDS: Signal to noise ratio, Principal component analysis, Sensors, Error analysis, Reflectivity, Gaussian filters, Digital imaging, Associative arrays, Algorithm development, Filtering (signal 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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