Convolutional Color Constancy

Color constancy is the problem of inferring the color of the light that illuminated a scene, usually so that the illumination color can be removed. Because this problem is underconstrained, it is often solved by modeling the statistical regularities of the colors of natural objects and illumination. In contrast, in this paper we reformulate the problem of color constancy as a 2D spatial localization task in a log-chrominance space, thereby allowing us to apply techniques from object detection and structured prediction to the color constancy problem. By directly learning how to discriminate between correctly white-balanced images and poorly white-balanced images, our model is able to improve performance on standard benchmarks by nearly 40%

Augmenting basic colour terms in english

In an unconstrained colour naming experiment conducted over the web, 330 participants named 600 colour samples in English. The 30 most frequent monolexemic colour terms were analyzed with regards to frequency, consensus among genders, response times, consistency of use, denotative volume in the Munsell and OSA colour spaces and inter-experimental agreement. Each of these measures served for ranking colour term salience; rankings were then combined to give a composite index of basicness. The results support the extension of English inventory from the 11 basic colour terms of Berlin and Kay to 13 terms by the addition of lilac and turquoise

A Paradigm for color gamut mapping of pictorial images

In this thesis, a paradigm was generated for color gamut mapping of pictorial images. This involved the development and testing of: 1.) a hue-corrected version of the CIELAB color space, 2.) an image-dependent sigmoidal-lightness-rescaling process, 3.) an image-gamut- based chromatic-compression process, and 4.) a gamut-expansion process. This gamut-mapping paradigm was tested against some gamut-mapping strategies published in the literature. Reproductions generated by gamut mapping in a hue-corrected CIELAB color space more accurately preserved the perceived hue of the original scenes compared to reproductions generated using the CIELAB color space. The results of three gamut-mapping experiments showed that the contrast-preserving nature of the sigmoidal-lightness-remapping strategy generated gamut-mapped reproductions that were better matches to the originals than reproductions generated using linear-lightness-compression functions. In addition, chromatic-scaling functions that compressed colors at a higher rate near the gamut surface and less near the achromatic axis produced better matches to the originals than algorithms that performed linear chroma compression throughout color space. A constrained gamut-expansion process, similar to the inverse of the best gamut-compression process found in this experiment, produced reproductions preferred over an expansion process utilizing unconstrained linear expansion

Colour Communication Within Different Languages

For computational methods aiming to reproduce colour names that are meaningful to speakers of different languages, the mapping between perceptual and linguistic aspects of colour is a problem of central information processing. This thesis advances the field of computational colour communication within different languages in five main directions. First, we show that web-based experimental methodologies offer considerable advantages in obtaining a large number of colour naming responses in British and American English, Greek, Russian, Thai and Turkish. We continue with the application of machine learning methods to discover criteria in linguistic, behavioural and geometric features of colour names that distinguish classes of colours. We show that primary colour terms do not form a coherent class, whilst achromatic and basic classes do. We then propose and evaluate a computational model trained by human responses in the online experiment to automate the assignment of colour names in different languages across the full three-dimensional colour gamut. Fourth, we determine for the first time the location of colour names within a physiologically-based cone excitation space through an unconstrained colour naming experiment using a calibrated monitor under controlled viewing conditions. We show a good correspondence between online and offline datasets; and confirm the validity of both experimental methodologies for estimating colour naming functions in laboratory and real-world monitor settings. Finally, we present a novel information theoretic measure, called dispensability, for colour categories that predicts a gradual scale of basicness across languages from both web- and laboratory- based unconstrained colour naming datasets. As a result, this thesis contributes experimental and computational methodologies towards the development of multilingual colour communication schemes

Modeling Perceptual Trade-offs for Designing HDR Displays

Display technology has evolved in pursuit of perceptual pleasure by providing realism and visual impact. The endeavor of the evolution has brought HDR displays to the market. HDR displays, which have become the mainstream display technology recently, are considered not only the present but also the future of displays because of their daunting technical goals: A peak luminance of 10,000 cd/m^2 and near-monochromatic primaries. However, both positive and negative prospects in terms of perceptual aspects for future HDR displays coexist. On the positive side, it is expected that HDR displays will provide better image quality and more vivid color. On the negative side, apart from technical barriers such as production cost and power consumption, HDR displays will induce side effects, for example, observer metamerism, which refers to the phenomenon that color matches for one observer result in color mismatches for other observers. This particular side effect could be a severe issue in HDR displays as their narrow-band primaries likely worsen the color mismatches. Hence, critical to the success of future HDR displays is dealing properly with the perceptual trade-offs. In other words, future HDR display designers need to select physical specifications that maximize perceptual benefits while minimizing adverse effects. This dissertation aims at exploring both potentially positive and negative aspects of future HDR displays, using various perceptual assessments. In particular, the dissertation focuses on two physical factors of a display device: peak luminance and chromaticity color gamut, and the effects of the two factors on related human perception: image quality, observer metamerism, and colorfulness. The ultimate goal of this dissertation is to address the related human perception aroused by the physical factors and propose models to help design future HDR displays. In order to achieve the goal, the dissertation first addresses the image quality trade-off relationship between peak luminance and chromaticity color gamut. A psychophysical experiment was used to develop models to predict equivalent image quality under the trade-off between peak luminance and chromaticity gamut as a function of the perceptual attributes lightness and chroma. Second, a novel approach based on a computational evaluation to investigate potential observer metamerism in HDR displays was explored. This research shows how observer metamerism in HDR displays varies with varying peak luminance and chromaticity color gamut. This research aims at developing a straightforward model to predict observer metamerism in HDR displays based on the computational evaluation. Third, a psychophysical experiment to derive a colorfulness scale for very saturated colors is carried out. This experiment focuses on understanding how the sensitivity of the human visual system responds to highly-saturated colors that extend beyond the stimuli studied in previous research. The colorfulness scale would help both advanced lighting system and display system designers. Fourth, the dissertation suggests an evaluation tool devised based on the observer metamerism and colorfulness scale works that can be utilized to determine the physical specification of HDR displays, maximizing perceptually positive effects while minimizing perceptually negative effects at the same time

The Use of English Colour Terms in Big Data

This study explores the use of English colour names in large datasets from informal Twitter messages and the well-structured corpus of Google Books. Because colour names in text have no directly associated chromatic stimuli, the corresponding colour categories of colour words was assessed from responses in an online colour naming experiment. A comparison of the frequency in the three datasets revealed that the mapping of colour names to perceptually uniform colour spaces does not reflect natural language colour distributions

Review of Fluorescence Guided Surgery Visualization and Overlay Techniques

In fluorescence guided surgery, data visualization represents a critical step between signal capture and display needed for clinical decisions informed by that signal. The diversity of methods for displaying surgical images are reviewed, and a particular focus is placed on electronically detected and visualized signals, as required for near-infrared or low concentration tracers. Factors driving the choices such as human perception, the need for rapid decision making in a surgical environment, and biases induced by display choices are outlined. Five practical suggestions are outlined for optimal display orientation, color map, transparency/alpha function, dynamic range compression, and color perception check