M. S.

This dissertation examines those attributes of full-color display systems (particularly color matrix displays) which degrade image quality. Based on this analysis, it is suggested that a comprehensive metric should measure image quality in terms of transmitted signal and noise modulation, both achromatic and chromatic. Moreover, it is suggested that these signal and noise measurements be weighted in terms of human spatial-chromatic visual characteristics. A review of extant image quality metrics reveals several limitations of these metrics which make them unsuitable for the evaluation of color matrix displays. These limitations include the inability to account for chromatic modulation transfer and chromatic noise as well as the general inability to account for spatial and grey-scale sampling. This work describes a new methodology for assessing image quality that can be applied to full-color as well as monochromatic, and sampled as well as continuous, display systems. Unlike most display quality metrics, the proposed methodology is not based on the tools of linear systems analysis. Rather, it is based on more veridical models of the human visual system (HVS), including multi-channel models of spatial vision, the zone theory of color vision, physiological models of retinal processes, and models of the optics of the eye. A display evaluation system consisting of the HVS model used in conjunction with a display simulator is described. The HVS model employs nine image processing stages to account for nonlinear retinal processes, opponent color encoding, and multiple spatial frequency channels. A detailed procedure for using the HVS model to evaluate display systems is provided. The validity of the HVS model was tested by conducting contrast detection, discrimination, and magnitude estimation experiments on the model. The results of these experiments correspond closely with published human performance data The utility of the display evaluation system was assessed by making image quality predictions for the display systems used in three image quality studies. Image quality predictions using the proposed system correlate strongly with ratings of image quality provided by human subjects. Results of these validation studies indicate that the proposed method of display evaluation is viable and warrants further development. / Ph. D.

The primary objective of this dissertation was to investigate the effects of varying levels of luminance, color, and spatial frequency content on the perceived image quality of a soft-copy color image. A secondary objective was to test the robustness of selected image quality metrics (MTFA, SQRI, and ICS) to the color variations as measured by the change in correlations between the perceived quality ratings and the values of the image quality metrics. To accomplish these objectives, a color image was selected and its luminance, color, and spatial frequency components were attenuated systematically using image processing software. With the manipulated images, an experiment was conducted in which subjects were asked to rate, on a 0.0 - 9.0 continuous scale, the perceived quality of a displayed image in comparison to the original image. Results of the statistical analysis of the collected data were characterized by the highly significant main effects and interaction effects. However, the magnitudes of the interactions were small. The effect of the luminance component on perceived quality was found to be dominant and consistent across all the levels of the other two variables. As the luminance increased, the perceived quality increased at a decreasing rate. The luminance main effect was modeled well (R² = 0.9968) by the second-order polynomial of the luminance attenuation level, or, equivalently, by the relative amount of the luminance contained in the image. The range of variation of perceived quality produced by the six luminance levels was about five units on a 0.0 - 9.0 continuous scale. It was concluded that perceived quality of the color image was determined primarily by the luminance component of the image. The effect of color on perceived quality was found to be smaller than expected. The range of variation in perceived quality produced by the six color levels was only a little over one unit on a 0.0 - 9.0 continuous scale. Perceived qualities increased at a decreasing rate as the level of color increased. However, the slope of the curve representing the color effect was smaller than that of the luminance effect The main effect of color was modeled well (R² = 0.9972) by the second-order polynomial of the color attenuation level, or, equivalently, by the relative amount of color contained in the image. Based on the findings of the color effect, two different roles of color in image perception are suggested. At extremely low luminance, color acts primarily as a facilitator of the luminance by providing more cues on the content of the image. At sufficiently high luminance, the increased perceived quality stems from the aesthetic characteristics of the color. Both highpass and lowpass filtering, on the average, caused about 1.5 units of degradation as compared to the unfiltered image in perceived image quality on a 0.0 - 9.0 continuous scale. The perceived quality of the unfiltered image was greater than that of the filtered images across all the levels of luminance and color attenuation except at a low luminance level. There was no significant difference between the perceived qualities of the highpass and lowpass filtered images. The R² of the second-order polynomial for image qUality metrics (MTFA, SQRI, and ICS) and the mean perceived qualities did not vary across the color variations in the image manipulations. That is, these image quality metrics were robust to the color variations when the relationship between the quality metric values and the actual perceived qualities was represented by the second-order polynomial. However, with the first-order model, the R² increased as the color level increased. The SQRI yielded higher R² values than did the MTFA and ICS metrics when the first-order model was used. Also, the range of variation of R² for the SQRI was smaller than that for the other two metrics. Therefore, it appears that the robustness of an image quality metric to the color variation is affected by the degree of non-linearity correction in the metric if the robustness is tested in the context of the straight-line relationship. / Ph. D.

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1982. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING / Includes bibliographical references. / by Poh Chuan Lim. / M.S.

The effectiveness of information visualization largely depends on the ease and accuracy with which users can access the information. Visual clutter in a display can detract from a user's ability to properly read the information. An ideal visualization needs to maximize the visibility of patterns and structure and minimize the clutter present. Thus far, there has been surprisingly little work done in finding quantitative ways to measure clutter in information visualizations. The goal of this project was to create clutter measurement and reduction techniques that minimize the presence of visual clutter and maximize a user's ability to accurately read the data. These methods were tested and evaluated on a number of visualizations depicting domestic air traffic data.

Thesis. 1978. M.S.--Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING. / Bibliography: leaf 125. / by Avram K. Tetewsky. / M.S.

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1980. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING. / Vita. / Bibliography: leaves 98-102. / by Brad Allen Myers. / M.S.

Thesis (Ph.D)--Computing, Georgia Institute of Technology, 2009. / Committee Chair: Stasko, John T.; Committee Member: Edwards, Keith; Committee Member: Greenberg, Saul; Committee Member: Grinter, Beki; Committee Member: Guzdial, Mark. Part of the SMARTech Electronic Thesis and Dissertation Collection.

Thesis (M. S.)--Literature, Communication, and Culture, Georgia Institute of Technology, 2009. / Committee Chair: Mazalek, Ali; Committee Member: Bolter, Jay David; Committee Member: Do, Ellen Yi-Luen; Committee Member: Nitsche, Michael; Committee Member: Winegarden, Claudia R.

The purpose of this research was to determine whether changes in the presentation format of items in a computer display could be used to alter the impact of specific cognitive biases, and to add to the knowledge needed to construct theory-based guidelines for output design. The problem motivating this study is twofold. The first part of the problem is the sub-optimal decision making caused by the use of heuristics and their associated cognitive biases. The second part of the problem is the lack of a theoretical basis to guide the design of information presentation formats to counter the effects of such biases. An availability model of the impact of changes in presentation format on biases and heuristics was constructed based on the findings of a literature review. A six-part laboratory experiment was conducted utilizing a sample of 205 student subjects from the college of business. The independent variable was presentation format which was manipulated by altering the visual salience or visual recency of items of information in a visual computer display. The dependent variables included recall, perceived importance, and the subjects' responses to three judgment tasks. The results clearly demonstrate that changes in presentation format can be used to alter the impact of cognitive biases on human decision making. The results also provide support for the availability model, with the exception of the proposed influence of learning style. Learning style was found to have no significant impact on decision making whether alone or in combination with changes in presentation format. The results of this investigation demonstrate that by using our knowledge of cognitive processes (e.g., the visual salience effect, the visual recency effect, and the availability heuristic), presentation formats can be altered in order to moderate the effects of certain biases and heuristics in human decision making. An understanding of these results may be useful in improving DSS design.