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Dissertation Abstracts International Section A: Humanities and Social Sciences ; 83(7-A):No Pagination Specified, 2022.
Article in English | APA PsycInfo | ID: covidwho-1823675

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. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

2.
29th Color and Imaging Conference - Color Science and Engineering Systems, Technologies, and Applications, CIC 2021 ; 2021-November:387-392, 2021.
Article in English | Scopus | ID: covidwho-1592995

ABSTRACT

Accurately describing the effect of lighting on color appearance phenomena is critical for color science education. While it is ideal to conduct in-person tutorials to demonstrate the color appearance fundamentals, laboratory tutorials have been limited due to COVID-19. The limitation of in-person gatherings and the increase popularity of remote teaching help evoke alternative methods to demonstrate color appearance phenomena. Here, a remote tutorial method is described, and results are compared to in-person tutorials. While the remote tutorial had weaker result in representing observers’ color experience compared to the in-person lab tutorial, remote demonstrations can be used to demonstrate and discuss the limitations of color imaging, and the difference between the human visual system and digital imaging systems. © 2021 Society for Imaging Science and Technology. All rights reserved.

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