Dr. Joyce E. Farrell
Senior Research Associate at Stanford Univ
SPIE Involvement:
Symposium Committee | Conference Co-Chair | Conference Program Committee | Author | Instructor
Publications (26)

SPIE Conference Volume | March 16, 2015

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

SPIE Journal Paper | May 14, 2014
OE Vol. 53 Issue 06
KEYWORDS: Human vision and color perception, Visual optics, Imaging systems, Eye, Optical engineering, Medical research, Biomedical optics, Systems engineering, Visual system, Light emitting diodes

PROCEEDINGS ARTICLE | March 7, 2014
Proc. SPIE. 9023, Digital Photography X
KEYWORDS: Submerged target modeling, Data modeling, Cameras, Signal attenuation, Calibration, Water, Light scattering, Photography, RGB color model, Absorption

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 | February 4, 2013
Proc. SPIE. 8660, Digital Photography IX
KEYWORDS: Signal to noise ratio, Hyperspectral imaging, Short wave infrared radiation, Data modeling, Imaging systems, Cameras, Reflectivity, Data conversion, Systems modeling, Line scan image sensors

Showing 5 of 26 publications
Conference Committee Involvement (10)
Digital Photography and Mobile Imaging XI
9 February 2015 | San Francisco, California, United States
SPIE/IS&T Electronic Imaging
8 February 2015 | San Francisco, United States
Digital Photography X
3 February 2014 | San Francisco, California, United States
Digital Photography IX
4 February 2013 | Burlingame, California, United States
Digital Photography IX
4 February 2013 | Burlingame, California, United States
Showing 5 of 10 published special sections
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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