Abstract

With the rise in high quality displays and cameras following the mainstream adoption of smartphones, image quality has become an essential aspect of engaging and attracting consumers. In the case of smartphones, the bar raises with release of every new generation. There are many factors affecting image quality such as sharpness, image noise or non-uniformity, and geometric distortion, but it is fair to say that color plays a vital role in the perceived quality of an image. Colors not only spark emotions and engage a user but also decide the likability of a certain image. Over the past few years computational photography techniques have become a major differentiating factor between camera manufacturers. These techniques are used to enhance certain features of an image such that it is more pleasing to the viewer. It is important to understand better the perceived and preferred image quality for pictures and to develop a procedure for evaluating them as a part of the camera/display development and design process. This dissertation focuses on exploring such preferred color image renderings using different methodologies of perceptual assessments. We focus on common scenes that contains memory objects such as grass, sky, skin tone, beach sand and food items. In particular, we also focus on white balance preference of an image which controls the appearance of the object in the scene under different illumination. The ultimate goal of this dissertation is to address how we perceive color quality and to develop procedures for its evaluation, and to assess preferred color image rendering. These results can be used to help design better cameras and displays by improving color image quality. In order to achieve the goal of the dissertation, we focus on investigating the preferred rendering of common scenes that contains memory objects, scenes captured under different illumination - controlled and uncontrolled light settings. First we address how we perceive memory colors, with and without pictorial scene content. Then we study the impact of different texture types on these memory colors, along with understanding the relationship between memory color and color quality preference. This dissertation also addresses the color quality of video conference calls using virtual backgrounds, which has been a common means of communication since COVID19 pandemic. In particular, it focuses on the preferred color balance for images with a foreground model against a virtual background. To further investigate the white balance preference settings, we assessed images where the foreground, containing a person, is illuminated by a different correlated color temperature (CCT) than the background, which includes several targets. Models having different skin tones were used.

Library of Congress Subject Headings

Imaging systems--Image quality; Colorimetry; Color vision; Teleconferencing

Publication Date

12-2021

Document Type

Dissertation

Student Type

Graduate

Degree Name

Color Science (Ph.D.)

Advisor

Nathan Cahill

Advisor/Committee Member

Susan P. Farnand

Advisor/Committee Member

Mary Carol Mazza

Campus

RIT – Main Campus

Plan Codes

CLRS-PHD

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