Foveal optical modulation transfer function of the human eye at various pupil sizes

We determined the foveal optical modulation transfer functions of the human eye (O) for pupil sizes of 1-8 mm by using two simple psychophysical techniques. O as a function of spatial frequency f could be described by exp[-(f/fc)n] at any pupil size in our data as well as in the data available in the literature [J. Physiol. (London) 186, 558 (1966); Opt. Acta 21, 395 (1974); Vision Res. 33, 15 (1993); J. Opt. Soc. Am. A 11, 246 (1994)]. When all these estimates of fc and n were pooled the parameters were found to depend on the pupil diameter as fc = 16.6 - 1.49p and n = exp(0.840/p - 0.318). This result indicates that at 1 mm O(f) is close to the diffraction-limited system.

A comparison of physical image quality indices and observer performance in the radiographic detection of nylon beads

Although various models have been proposed in an attempt to predict the usefulness of a radiographic image in terms of its physical characteristics, no previous work has shown whether a single physical image quality index, such as a signal-to-noise ratio, can reliably predict the performance of a human observer over a broad range of image characteristics. We studied the relationship between physical and visual image quality for the task of detecting nylon beads in radiographs. Thirty-seven imaging cases with different combinations of physical image characteristics were considered; these included variations in object size and magnification, X-ray beam quality, screen-film system, screen-film contact, film density and illumination, and viewing distance. For each imaging case, visual image quality was quantified in terms of observer performance in a 2AFC visual detection experiment. Physical image quality indices were calculated according to eight different models of the detection process; these indices combined data regarding object size and attenuation, screen-film system MTF, film gradient, noise Wiener spectrum, and visual system response. The results of this work indicate that, for the conditions studied, human observer detection performance most closely resembles that of a sub-optimal statistical decision process.

Flying spot TV ophthalmoscope

We have designed a recording ophthalmoscope which requires substantially less light than conventional ophthalmoscopes or fundus cameras. A laser beam of <100-microW total power provides the flying spot on the subject's retina, allowing an inversion of the usual division of the pupil: only the central half-millimeter is needed for illumination, and the remaining 50 mm(2) are used for light collection. No optical image of the retina is formed, but a photomultiplier tube in a pupillary conjugate plane provides video signals to a TV monitor, where an image appears. A simple analysis explains the gain in sensitivity. Various manipulations of the image are described, some of which are uniquely possible with this system.

Performance of the intensified electron-bombarded silicon camera tube in low-light-level television systems

The combination of an image intensifier and a TV pickup tube incorporating the electron-bombarded silicon gain storage target is one of the more promising new sensors now available for low-light-level imaging. In this paper, the resolution vs irradiance characteristics of this sensor are predicted using the electrical parameters of the sensor and the observer requirements as derived from psychophysical experimentation. Analytically derived results, which include the obherver as an integral part of the sensory system, are shown to be in good agreement with experimentally measured results.

Detection of TV Imagery by Humans vs Machines

The probability of detection of moving small and point targets embedded in random, white noise on a TV display has been measured for the human observer and compared to the observer's performance for detection of larger images; the improvement in detection performance by the insertion of cues onto the TV display is shown; and the probability of detection by machine-processed pattern recognition techniques is compared to the performance of the human observer.