James O. Larimer

Evaluation of human vision models for predicting human observer performance

We demonstrate that human-vision-model-based image quality metrics not only correlate strongly with subjective evaluations of image quality but also with human observer performance on visual recognition tasks. By varying amorphous silicon image system design parameters, the performance of human observers in target identification using the resulting test images was measured, and compared with the target weighted just-noticeable-difference produced by a human vision model applied to the same set of images. The detectability of model observer with the human observer was highly correlated for a wide range of image system design parameters. These results demonstrate that the human vision model can be used to produce human observer performance optimized imaging systems without the need for extensive human trials. The human vision based tumor detectors represent a generalization of channelized Hotelling models to non-linear, perceptually based models.

Studies of the field-of-view resolution tradeoff in virtual-reality systems

Most virtual-reality systems use LCD-based displays that achieve a large field-of-view at the expense of resolution. A typical display will consist of approximately 86,000 pixels uniformly distributed over an 80-degree by 60-degree image. Thus, each pixel subtends about 13 minutes of arc at the retina; about the same as the resolvable features of the 20/200 line of a Snellen Eye Chart. The low resolution of LCD-based systems limits task performance in some applications. We have examined target-detection performance in a low-resolution virtual world. Our synthesized three-dimensional virtual worlds consisted of target objects that could be positioned at a fixed distance from the viewer, but at random azimuth and constrained elevation. A virtual world could be bounded by chromatic walls or by wire-frame, or it could be unbounded. Viewers scanned these worlds and indicated by appropriate gestures when they had detected the target object. By manipulating the viewers field size and the chromatic and luminance contrast of annuli surrounding the field-of-view, we were able to assess the effect of field size on the detection of virtual objects in low-resolution synthetic worlds.

The Impact Of Boundaries On Color: Stabilized Image Studies

The NTSC standard for color television codes the chrominance signals at a lower spatial resolution than it codes the luminance signal. These differential resolutions result in a smearing of the colors in the scene relative to the edges that define objects, but television viewers are rarely aware of this degradation of the image because the human visual system also codes chrominance (i.e. hue) at a lower spatial resolution than it codes luminance (i.e. edges). Given the resolution difference for chrominance and luminance edges, a model of visual perception must explain why human observers do not perceive the color of objects flowing beyond the luminance edges of those objects. The internal chromatic aspects of objects, which may be determined at chrominance object-boundaries, may be constrained by the perceived spatial luminance boundaries of those objects. In the experiments that we will describe, a spatial chrominance and luminance boundary is prevented from moving on the viewers retina by moving it image synchronously with eye movements. When the edge is stabilized on the retina, the appearance of the image depends upon the enclosing boundaries that are not stabilized on the retina. We have found that the appearance of the image, independently of the images actual spatial energy distribution on the retina affects the ability of the human visual system to process information. For example, the viewers flicker sensitivity depends upon the perceived color of the image and not its actual spectral energy distribution. The same is true for the perceived color of a small spot imaged on the stabilized fields.

X-ray image system design using a human visual model

Because of the complex response of the human visual system, typical measurements of image system quality such as the detective quantum efficiency, mean transfer function, and signal-to- noise ratio cannot always be used to determine conditions for optimal perceptual image quality. Using a model of the human vision system, the ViDEOS/Sarnoff Human Vision Discrimination Model (HVM), this work demonstrates that human vision models provide a promising quantitative measure of image perceptual quality. The model requires an image and a matching reference image in order to determine the perceptual difference between the images at each point. A simple model of a digital amorphous silicon medical x-ray system is used to create the necessary images as a function of various design parameters. The image pairs are then analyzed by the HVM. In all cases the dependence of perceived image quality closely follows measures of image quality as determined by the HVM for many image system design variations. Increasing the detector size actually increases the image quality in the presence of either readout or input noise. The model was also used to optimize the image system for a specific task optimization. As an example, the effect of system design parameters on tumor identification in mammographic images is determined.

Avoiding on‐screen metamerism in N‐primary displays

— The present paper describes a method for using more than three primaries in an additive-primary display. The method ensures that each tristimulus specification can be produced in no more than one way, even if a non-singular filter (i.e., one that does not reduce the dimensionality of color-matching space) is interposed between the screen and the viewer. Starting with N primaries, the method uses only three at a time, but these may be composites — fixed linear combinations of the original N. As further insurance against on-screen metamerism, a criterion on the primary spectra, based on the Binet-Cauchy theorem, ensures that a triad of primaries keeps its right/left-handed chromaticity ordering when a filter is interposed.

Color appearance of filled-in backgrounds affects hue cancellation, but not detection thresholds

A long-wavelength background can affect the appearance of an increment of light superimposed upon it in two ways. It can change the visual systems sensitivity to the increment, and it can change the appearance of the increment by directly adding redness to it. Through selective retinal-image stabilization, we evoked the filling-in phenomenon to change the appearance of 640- and 575-nm backgrounds. Either of these backgrounds could be made to appear red or yellow, depending upon whether it was viewed under stabilized or unstabilized conditions. When the appearance of the 640-nm background was altered by filling-in to appear less red, test probes superimposed upon it required less 540-nm component to achieve an equilibrium hue. Increment thresholds measured on the 640- and 575-nm backgrounds, however, did not change with the appearance of the backgrounds.

Display characterization by eye: contrast ratio and discrimination throughout the grayscale

We have measured the ability of observers to estimate the contrast ratio (maximum white luminance / minimum black or gray) of various displays and to assess luminous discrimination over the tonescale of the display. This was done using only the computer itself and easily-distributed devices such as neutral density filters. The ultimate goal of this work is to see how much of the characterization of a display can be performed by the ordinary user in situ, in a manner that takes advantage of the unique abilities of the human visual system and measures visually important aspects of the display. We discuss the relationship among contrast ratio, tone scale, display transfer function and room lighting. These results may contribute to the development of applications that allow optimization of displays for the situated viewer / display system without instrumentation and without indirect inferences from laboratory to workplace.

Evaluation of image compression artifacts with ViDEOS: a CAD system for LCD color display design and testing

Transmission bandwidth and memory, even with the trend of increased availability and lower costs, are resources always in demand and their use needs to be opthnized. From all the elements of information in digital form, images are the top consumers of memory and bandwidth. Therefore, image compression is becoming a tool of general use for storage and transmission purposes, bringing along conspicuous image degradation. Visually perceived degradation needs to be quantified in order to make appropriate decisions involving compression tradeoffs for different imaging applications. The ViDEOS (Video Display Engineering and Optimization System) project is a software system under development. It is a computational tool for engineering color LCD displays under different sets of specifications and evaluating performance under different conditions. Multiple levels of a design can be analyzed with ViDEOS without having to build expensive prototypes; from the electro-optical performance of specific crystal interfaces to image rendering of a complete design under different settings of trade-off parameters. One of the capabilities of the VIDEOS system is the prediction of image visibility when viewed on any display represented within the system. This capability is implemented by means of a model of human vision which is part of the VIDEOS system. One of the many interesting applications is evaluating the visibility of image artifacts like those produced by image compression. Our ongoing efforts reported here include producing images at different degrees of compression and then comparing decompressed versions with respect to the original image using the vision model.

31:3 Judder‐Induced Edge Flicker at Zero Spatial Contrast

Judder is a motion artifact that degrades the quality of video imagery. Smooth motion appears jerky and can appear to flicker along the leading and trailing edge of the moving object. In a previous paper (1) we demonstrated that the strength of the edge flicker signal depended upon the brightness of the scene and the contrast of the moving object relative to the background. Reducing the contrast between foreground and background reduced the flicker signal. In this report, we show that the contrast signal required for judder-induced edge flicker is due to temporal contrast and not simply to spatial contrast. Bars made of random dots of the same dot density as the background exhibit edge flicker when moved at sufficient rate.

Hyperacuity on high-resolution and very high resolution displays

A vernier acuity task was used to compare three electronic displays, a high-resolution CRT, a high-resolution AMLCD, and a very-high-resolution AMLCD. The offset threshold value, approximately 6 seconds arc, was found to be independent of display resolution. The very-high-resolution display had one octave more positional accuracy than the high-resolution displays. This performance difference was readily apparent. To match the image quality of print or photographic reconstruction, a very-high-resolution screen is required.