Digital cameras are designed by teams of engineers and scientists who use different analytical tools to characterize each of the imaging components in the camera that they work on. Typically, these engineers specialize in the design and manufacturing of one imaging component, such as a lens, filter, sensor, processor, or display.

Achieving a high quality output from the camera, however, depends on multiple system components, including the optical system, imaging sensor, image processor, and display device working in consort. But analyzing these components individually, without reference to the characteristics of the other components, provides only a limited idea of the final performance of a system.

In an attempt to resolve that issue, Dr. Joyce Farrell and a team of researchers at Stanford University (Stanford, CA, USA) have now modeled and simulated the complete imaging pipeline of a digital camera, beginning with a radiometric description of the scene captured by the camera and ending with a radiometric description of the final image as it appears on an LCD display.

The result of their work is the Image Systems Evaluation Toolbox (ISET) -- a collection of software modules that now enables teams of camera designers to evaluate how both hardware components and algorithms influence the image quality of their products.

To market the ISET software -- which is based on the Matlab programming environment and image processing toolbox from the Mathworks (Natick, MA, USA) -- Stanford’s Farrell and Dr. Brian Wandell have founded their own company ImagEval Consulting. Readers who contact ImagEval can download a free demo version of the software.

Editor's note: The researchers published the details of the software earlier this year in the Optical Society of America's learned journal Applied Optics. The article entitled "Digital camera simulation" can be found here.

Recent articles on Matlab software that you might also find of interest.

1. Matlab helps speed software development of thermal cameras at FLIR

Engineers at FLIR Systems (Wilsonville, OR, USA) have turned to software from The Mathworks (Natick, MA, USA) to help them develop and deploy new algorithms for the company's range of thermal infra-red cameras.

2. Autonomous vehicle images apple orchard yields

Engineers at the Robotics Institute at Carnegie Mellon University have developed a computer vision-based system that can accurately estimate the yields from orchards of apple trees.

3. Vision system grades eggs

Researchers from the University of Kuala Lumpur (Kuala Lumpur, Malaysia) have developed a prototype image processing system to classify commercial eggs into their respective grades.

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-- Dave Wilson, Senior Editor, Vision Systems Design