Identification and Assignment of Colorimetric Observer Categories and Their Applications in Color and Vision Sciences
My PhD thesis focused on the effect of observer color perception variability (also called observer metamerism) in modern displays with narrow-band primaries. Through experiments and theoretical analyses, this work showed that (color normal) observers perceive colors quite differently, and this can be a major issue in color-critical professional applications involving modern wide-gamut displays. In particular, this variability becomes apparent when colors are compared on two systems with very different spectral power distributions.
In addressing this issue, we envisaged a new color processing framework called Observer-dependent Color Imaging, which would help us achieve personalized color processing. This addresses a fundamental limitation of colorimetry, which assumes a single observer model can reasonably represent the whole population of color normal observers. As part of this thesis research, a method was developed to classify observers as belonging to one of the seven representative observer categories (or models) derived through statistical analysis.
A low-cost, portable, early
proof-of-concept prototype called "Observer Calibrator" was developed for classifying color normal observers based
on their color vision. The prototype is equipped with two trichromatic LED light
sources with very different spectral characteristics (highly
metameric). In each trial, different versions of color matches are
shown in a bipartite field, where each version corresponds to an
observer category (or model). For a given observer, the version
consistently producing superior matches over several trials gives
his/her category. Such a device or method can not only address observer
metamerism, but can also prove extremely useful in general color
research that involves visual experiments. Collaborative experiments were performed in February 2011
with two laboratories in Europe involved in color research.
At Technicolor Research & Innovation, I received guidance from Dr. Laurent Blondé and Dr. Jürgen Stauder, (Principal Scientists), and a major developmental support from Mr. Patrick Morvan (Researcher). At the university, my advisor was Prof. Patrick Le Callet and co-advisor was Dr. Florent Autrusseau.
Full thesis is available here (6.6 MB).
Eight observer categories (i.e. color-matching functions) derived as part of this work are available here as an excel spreadsheet.
Following publications have so far resulted from this work:
This PhD thesis resulted in two patent applications:
MS Color Science Thesis Research
Evaluation of the Color Image and Video Processing Chain and Visual Quality Management for Consumer Systems
The research was sponsored by Intel Corp. My advisor was Prof. Mark Fairchild.
Abstract: With the advent of novel digital display technologies, color processing is increasingly becoming a key aspect in consumer video applications. Today’s state-of-the-art displays require sophisticated color and image reproduction techniques in order to achieve larger screen size, higher luminance and higher resolution than ever before. However, from color science perspective, there are clearly opportunities for improvement in the color reproduction capabilities of various emerging and conventional display technologies. This research seeks to identify potential areas for improvement in color processing in a video processing chain. As part of this research, various processes involved in a typical video processing chain in consumer video applications were reviewed. Several published color and contrast enhancement algorithms were evaluated, and a novel algorithm was developed to enhance color and contrast in images and videos in an effective and coordinated manner. Further, a psychophysical technique was developed and implemented for performing visual evaluation of color image and consumer video quality. Based on the performance analysis and visual experiments involving various algorithms, guidelines were proposed for the development of an effective color and contrast enhancement method for images and video applications. It is hoped that the knowledge gained from this research will help build a better understanding of color processing and color quality management methods in consumer video.
Full thesis is available here (compressed PDF: 41 MB). Individual chapters are available below, also in PDF format:
Chapter 0: Abstract, Acknowledgment, Table of Contents etc
Chapter 1: Introduction
Chapter 2: Color Video Processing
Chapter 3: Video Quality Assessment
Chapter 4: Methods for Color and Contrast Enhancement in Images and Video
Chapter 5: Implementation and Performance Analysis of Several Color/Contrast Enhancement Algorithms (15 MB)
Chapter 6: Psychophysical Evaluation of Three Algorithms (Compressed PDF: 31 MB)
Chapter 7: Conclusions
Appendix A: Algorithm Performance Analysis Plots (Compressed PDF: 20 MB)
A paper was published in Color Imaging Conference in November 2008. A draft of the paper is available here.
This MS thesis resulted in a patent application:
A. Sarkar, J.E. Caviedes, and M. Subedar, “Joint enhancement of lightness, color and contrast of images and video”, US Patent Application #20100085487 filed by Intel Corporation on September 30, 2008
Independent Research: Lighting
A Proof-Of-Concept Application of Digital Imaging in Lighting Control - Integrating Daylight and Occupancy Sensing
In February 2007, I completed this independent research project on a new and interesting application of a high dynamic range CMOS image sensor originally developed for automotive video applications. The project was funded by my department, the Center for Imaging Science (CIS) under the CIS-Kodak Grant for Innovative Graduate Student Research Proposals. Prof. Mark Fairchild and Prof. Carl Salvaggio were my advisors. This was a continuation of my MS thesis research at Penn State. Here is a draft of the paper published in Electronic Imaging 2008, San Jose, CA.
MS Lighting Thesis Research
This page was last modified on July 15, 2013. Modified 10 times since 28th July 2008.
Copyright© Abhijit Sarkar 2011. All rights reserved.