Jennifer Gille

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.

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.

The radon image as plenoptic function

We introduce a novel plenoptic function that can be directly captured or generated after the fact in plenoptic cameras. Whereas previous approaches represent the plenoptic function over a 4D ray space (as radiance or light field), we introduce the representation of the plenoptic function over a 3D plane space. Our approach uses the Radon plenoptic function instead of the traditional 4D plenoptic function to achieve 3D representation - which promises reduced size, making it suitable for use in mobile devices. Moreover, we show that the original 3D luminous density of the scene can be recovered via the inverse Radon transform. Finally, we demonstrate how various 3D views and differently-focused pictures can be rendered directly from this new representation.

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.

P‐46: Optimization of Subpixel Color Tiles for Mobile Displays

A key issue for the optimization of subpixel color tiles for mobile displays is to maximize the image quality, often defined in terms of brightness or reflectance, and color saturation, while minimizing display power consumption. for the mirasol™ display based on MEMS technology, the RGBY quad is found to be a structure that achieves a balance between reflectance and color saturation. Simulation results based upon demonstration devices are presented with discussions about proper image quality metrics for mobile displays.

20.4: Distinguished Paper: Optimizing the Brightness of Reflective Displays in Mobile Applications

Reflective display brightness is studied in mobile devices as a function of relevant ambient conditions, supplemental frontlight illumination, and display reflectance properties. Results for varying scattering properties in specular modulator-based displays such as mirasol®, as well as combinations of ambient and internal frontlight illumination conditions for optimizing the user experience across various lighting environments are presented.

Improving the appearance of flat-panel displays using multilevel color error diffusion

A tool written in MatLab is described that can be used to simulate display devices. Images as they would appear on the simulated display can be rendered on a workstation screen for direct visualization of the simulated data. The tool also produces a two-dimensional matrix of CIE XYZ vectors that corresponds to the photometric measure of the simulated display with an image rendered on it. This tool is part of a larger effort to build a CAD tool for flat panel display design and optimization. Use of the tool is illustrated with examples of multi-level error diffusion. An empirical experiment is described comparing the predictions of the CAD tool set to actual human performance. The system is found to be consistent with human psychophysics and useful for device design and optimization.

Gray-scale/resolution tradeoff

Spatial resolution and grayscale resolution are two image parameters that determine image quality. In this study we investigate the trade-off between spatial resolution and grayscale in terms of the discriminability of steps, measured in bits, away from a standard image. A CRT display was used to simulate black-and-white images with a square-pixel geometry. Natural images and a test pattern consisting of a radially symmetric spatial frequency chirp of increasing radial frequency (called a zone plate) were studied. Multiple versions of each image were produced by varying the simulated pixel size and the number of gray levels and by filtering. Discrimination thresholds for pixel size and number of gray levels were measured for several locations in the parameter space of spatial resolution and grayscale resolution for each image. Unfiltered, low-contrast, Nyquist-filtered, and Gaussian-filtered versions of the images were studied. Resolution levels were always integer divisors of the CRT display resolution, produced by subsampling and pixel-replication. Gray levels were steps that were linear in luminance and that spanned the entire CRT luminance range. Discrimination thresholds were measured using a three-alternative forced-choice one-up-two-down double- random-staircase procedure. Simulation device limitations caused some measurements to be less precise than was desired.

Challenges in Display Color Management (DCM) for Mobile Devices

Systematic and effective color management for displays on mobile devices is becoming increasingly more challenging. A list of the main challenges includes (a) significant differences in display technologies, (b) significant display color response and tone response variability, (c) significant display color gamut variability, (d) significant content gamut variability, (e) mixing content with different color gamuts, (f) Significant variability in viewing conditions and (g) significant mobile display power consumption. This paper will provide general descriptions of the above challenges, their characteristics and complexities.