Engineering Approach to Imaging Systems Design
The imaging system analyst must be conversant in numerous diverse technologies. Each has a unique effect on system evaluation. This course highlights these technologies in 10 sections and is filled with numerous practical and useful examples. While the equations are provided, the concepts are presented graphically and with imagery. An engineering approach is taken: the "bare bones" imaging system consists of illumination, optics, detector, and display. The radiometry and photometry section compares calibration sources to real sources (sun, fading twilight, artificial sources). The optics/detector combination performance can be described in the frequency domain (MTF analysis) by the parameter Fλ/d which is the ratio of the detector cutoff to the optics cutoff. Equally important, but often neglected is sampling; an inherent feature of all electronic imaging systems. Sampling artifacts, which creates blocky images, are particularly bothersome with periodic targets such as test targets and bar codes. Sampling cannot be studied in isolation but requires a reconstruction filter. Sampling artifacts are illustrated through numerous imagery. For man-in-the-loop operation, the display and the eye are of concern and, in many situations, these limit the over system performance. The impact of viewing distance on the image quality of displays, TVs, computers, cell phones, and halftones is discussed. A point-and-shoot camera appears simplistic from the outside. However, as shown in an example, modeling can be quite complex.
The math, statistics, and data analysis section covers the validity of approximations, central limit theorem, Gaussian statistics, decision theory, and the receiver operating curve (ROC). Included are different ways to graph data and, as an example, the margin of error reported in political polls. System resolution (a.k.a. image quality) can be inferred from Schade's equivalent resolution which is a function of Fλ/d. Atmospheric transmittance and glare (via the sky-to-ground ratio) is discussed.
Target acquisition is presented with a simplified, back-of-the-envelope, approach using Fλ/d. Early systems had "large" detectors (Fλ/d < 0.5). These systems were detector limited and acquisition range was inversely proportional to detector size. With "small" detectors (Fλ/d > 1.5) the system is optics limited. Here changing the detector size has minimal effect on range. Selecting a mid-wave (MWIR) or long-wave (LWIR) infrared sensor depends upon Fλ/d, sensor noise, and atmospheric conditions.
This course will enable to you to
- Use approximations appropriately (often called "rule-of-thumb," or "back-of-the-envelope" analysis)
- Understand the difference between resolution limited, sensitivity limited, detector-limited, and optics-limited
- Determine which subsystem limits system performance and why
- Understand sampling artifacts (Nyquist frequency limit, aliasing, Moiré patterns, and variations in object edge location and width)
- Use MTFs, resolution, sensitivity, and sampling concepts for system optimization
- Understand the trade off between MTF and aliasing.
The course is for managers, system designers, test engineers, integrators, machine vision specialists, and camera users who want the best performance from their systems. It is helpful if the students are familiar with linear system theory (MTF analysis).
Course level: Introductory
Course length: full day
Gerald Holst is an independent consultant for imaging system analysis and testing. He was a technical liaison to NATO, research scientist for DoD, and a member of the Lockheed-Martin senior technical staff. Dr. Holst has chaired the SPIE conference Infrared Imaging Systems: Design, Analysis, Modeling and Testing since 1989. He is author of over 30 journal articles and 6 books (published by SPIE and/or JCD Publishing). Dr. Holst is a member of OSA and is a SPIE Fellow.
Holst's Practical Guide to Electro-Optical Systems (JCD Publishing, 2003) by Gerald C. Holst.
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