Image Systems

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Two main software developments have emerged from our work. One is the suite of tools we call the [http://imageval.com Image Systems Engineering Toolbox]. These tools are designed for simulation of image systems hardware. This work is under active development by several members of our group, including extensions into computer graphics, computer vision, and machine learning.
Two main software developments have emerged from our work. One is the suite of tools we call the [http://imageval.com Image Systems Engineering Toolbox]. These tools are designed for simulation of image systems hardware. This work is under active development by several members of our group, including extensions into computer graphics, computer vision, and machine learning.
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A second, related project emphasizes modeling biological image systems. This project, supported by the Simons Foundation, is [http://web.stanford.edu/~ej/computational-eye-brain/ Computational Eye-Brain], is joint with David Brainard,  E.J. Chichilnisky and Fred Rieke.  The software that initiated that project is an ISET spinoff that we call ISET for Biology (ISETBIO).  The open-source code is hosted  [https://github.com/isetbio/isetbio as ISETBIO on github].  ISET and ISETBIO have now diverged, with each containing different core features.
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A second, related project emphasizes modeling biological image systems. This project, supported by the Simons Foundation, is [http://web.stanford.edu/~ej/computational-eye-brain/ Computational Eye-Brain], is joint with David Brainard,  E.J. Chichilnisky and Fred Rieke.  The software that initiated this project is open-source and hosted  [https://github.com/isetbio/isetbio as ISETBIO on github].  The [https://github.com/isetbio/isetbio/wiki ISETBIO wiki page] describes that work.
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ISET and ISETBIO have diverged, so that while they overlap in many ways they also contain different capabilities.  
= Image quality metrics =
= Image quality metrics =

Revision as of 14:55, 26 November 2015

Our lab develops algorithms and software for to image systems engineering. We do this work as part of Stanford's Center for Image Systems Engineering, a program whose participants work on devices and algorithms for displays, cameras, computer graphics, and computer vision.

Our work focuses on simulations of the image systems pipeline from describing the scene, through optics, sensors, image processing and displays. We are particularly connected to features of the image system pipeline that relate with the human visual system and image quality metrics, but we also do work specifically for engineering applications.

Two main software developments have emerged from our work. One is the suite of tools we call the Image Systems Engineering Toolbox. These tools are designed for simulation of image systems hardware. This work is under active development by several members of our group, including extensions into computer graphics, computer vision, and machine learning.

A second, related project emphasizes modeling biological image systems. This project, supported by the Simons Foundation, is Computational Eye-Brain, is joint with David Brainard, E.J. Chichilnisky and Fred Rieke. The software that initiated this project is open-source and hosted as ISETBIO on github. The ISETBIO wiki page describes that work.

ISET and ISETBIO have diverged, so that while they overlap in many ways they also contain different capabilities.

Contents

Image quality metrics

CIELAB metrics

Spatial CIELAB

vSNR

Reference free metrics

Engineering metrics

PSNR

Multispectral imaging

Sensors

Presentations

SPIE tutorials

We have given a variety of tutorials and classes on color vision, digital imaging, and sensors. Notes from these classes as well as some ongoing writing projects are linked here.

SPIE sensor modeling and image quality evaluation tutorial 2010 (Wandell, Farrell, Catrysse)

(2006, 2007, 2008, 2009)

PGE tutorial

Applied Vision and Image Systems Engineering (Psych 221)

Notes from class?

Personal tools