Gamut extension algorithm development and evaluation for the mapping of standard image content to wide-gamut displays

Wide-gamut display technology has provided an excellent opportunity to produce visually pleasing images, more so than in the past. However, through several studies, including Laird and Heynderick, 2008, it was shown that linearly mapping the standard sRGB content to the gamut boundary of a given wide-gamut display may not result in optimal results. Therefore, several algorithms were developed and evaluated for observer preference, including both linear and sigmoidal expansion algorithms, in an effort to define a single, versatile gamut expansion algorithm (GEA) that can be applied to current display technology and produce the most preferable images for observers. The outcome provided preference results from two displays, both of which resulted in large scene dependencies. However, the sigmoidal GEAs (SGEA) were competitive with the linear GEAs (LGEA), and in many cases, resulted in more pleasing reproductions. The SGEAs provide an excellent baseline, in which, with minor improvements, could be key to producing more impressive images on a wide-gamut display

Fully-automatic inverse tone mapping algorithm based on dynamic mid-level tone mapping

High Dynamic Range (HDR) displays can show images with higher color contrast levels and peak luminosities than the common Low Dynamic Range (LDR) displays. However, most existing video content is recorded and/or graded in LDR format. To show LDR content on HDR displays, it needs to be up-scaled using a so-called inverse tone mapping algorithm. Several techniques for inverse tone mapping have been proposed in the last years, going from simple approaches based on global and local operators to more advanced algorithms such as neural networks. Some of the drawbacks of existing techniques for inverse tone mapping are the need for human intervention, the high computation time for more advanced algorithms, limited low peak brightness, and the lack of the preservation of the artistic intentions. In this paper, we propose a fully-automatic inverse tone mapping operator based on mid-level mapping capable of real-time video processing. Our proposed algorithm allows expanding LDR images into HDR images with peak brightness over 1000 nits, preserving the artistic intentions inherent to the HDR domain. We assessed our results using the full-reference objective quality metrics HDR-VDP-2.2 and DRIM, and carrying out a subjective pair-wise comparison experiment. We compared our results with those obtained with the most recent methods found in the literature. Experimental results demonstrate that our proposed method outperforms the current state-of-the-art of simple inverse tone mapping methods and its performance is similar to other more complex and time-consuming advanced techniques

High Dynamic Range (HDR) Display Perception

Displays have undergone a huge development in the last several decades. From cathode-ray tube (CRT), liquid crystal display (LCD), to organic light-emitting diode (OLED), even Q-OLED, the new configurations of the display bring more and more functions into industry and daily life. In the recent several years, high dynamic range (HDR) displays become popular. HDR displays usually refer to that the black level of the display is darker and the peak being brighter compared with the standard dynamic range (SDR) display. Traditionally, the peak luminance level can be used as the white in characterization and calibration. However, for HDR displays, the peak luminance is higher than the traditional diffuse white level. Exploration of the perceptual diffuse white in HDR image when presented in displays is proposed, which can be beneficial to the characterizing and the optimizing the usage of the HDR display. Moreover, in addition to the ``diffuse white , 3D color gamut volume can be calculated in some specific color appearance models. Calculation and modeling of the 3D color gamut volume can be very useful for display design and better characterizing display color reproduction capability. Furthermore, the perceptional color gamut volume can be measured through psychophysical experiments. Comparison between the perceptional color gamut volume and the theoretical 3D gamut volume calculations will reveal some insights for optimizing the usage of HDR displays. Another advantage of the HDR display is its darker black compared with the SDR display. Compared with the real black object, what level of black is `perfect\u27 enough in displays? Experiments were proposed and conducted to evaluate that if the HDR display is capable of showing ``perfect black for different types of background images/patterns. A glare-based model was proposed to predict the visual ``perfect black. Additionally, the dynamic range of human vision system is very large. However, the simultaneous dynamic range of human vision system is much smaller and is important for the fine tuning usage of HDR displays. The simultaneous dynamic range was measured directly for different stimulus sizes. Also, it was found that the simultaneous dynamic range was peak luminance level dependent. A mathematical model was proposed based on the experimental data to predict the simultaneous dynamic range. Also the spatial frequency effect of the target pattern on the simultaneous dynamic range was measured and modeled. The four different assessments about HDR displays perception would provide experimental data and models for a better understanding of HDR perception and tuning of the HDR display

Uniform color spaces based on CIECAM02 and IPT color difference equations

Color difference equations based on the CIECAM02 color appearance model and IPT color space have been developed to fit experimental data. There is no color space in which these color difference equations are Euclidean, e.g. describe distances along a straight line. In this thesis, Euclidean color spaces have been derived for the CIECAM02 and IPT color difference equations, respectively, so that the color difference can be calculated as a simple color distance. Firstly, the Euclidean line element was established, from which terms were derived for the new coordinates of lightness, chroma, and hue angle. Then the spaces were analyzed using performance factors and statistics to test how well they fit various data. The results show that the CIECAM02 Euclidean color space has performance factors similar to the optimized CIECAM02 color difference equation. To statistical significance, the CIECAM02 Euclidean color space had superior fit to the data when compared to the CIECAM02 color difference equation. Conversely, the IPT Euclidean color space performed poorer than the optimized IPT color difference equation. The main reason is that the line element for the lightness vector dimension could not be directly calculated so an approximation was used. To resolve this problem, a new IPT color difference equation should be designed such that line elements can be established directly

Façade colour and aesthetic response: Examining patterns of response within the context of urban design and planning policy in Sydney

The overall aim of this research was to examine aesthetic response to façade colour. Drawing on a range of theories and studies from environment-behaviour studies (EBS), Nasar’s (1994) probabilistic model of aesthetic response to building attributes provided a theoretical framework within which to examine patterns of response. Prompted by the Development Control Plan for Sydney Regional Environmental Plan: Sydney Harbour Catchment (NSWDOP, 2005), this research also linked its aims and methods to planning policy in Sydney. The main research questions focussed on whether changes in aesthetic response are associated with variations in façade colour; and whether changes in judgements about building size, congruity and preference are associated with differences in façade colour. A quasi-experimental research design was used to examine patterns of aesthetic response. The independent variable was represented by four façade colours in two classifications. An existing process, environmental colour mapping, was augmented with digital technology and used to isolate, identify and manipulate the independent variable and for preparation of visual stimuli (Foote, 1983; Iijima, 1995; Lenclos, 1977; Porter, 1997). Façade colour classifications were created from extant colour theories (including those of Albers, 1963; Hard & Sivik, 2001 and Itten, 1961). The façade colour classifications were further developed using F-sort and Q-sort methodology (Amin, 2000; Miller, Wiley & Wolfe, 1986; Stephenson, 1953). Ten dependent variables, linked to overall aesthetic response, were drawn from studies relating to environmental evaluation, building congruity and preference (Groat, 1992; Janssens, 2001; Russell, 1988; Russell, 2003; Russell, Ward & Pratt, 1981; Wohlwill & Harris, 1980). The dependent variables were presented in the form of a semantic differential rating scale and a sample group of 288 evaluated the visual stimuli. The Latin-square technique was used for the controlled presentation of visual stimuli. Factor analysis, correlation analysis and analysis of variance were applied to the data. The findings indicate that variations in aesthetic response are associated with differences in façade colour. Judgements about building size varied by up to 5% and buildings featuring contrasting façade colours were judged to be larger and more dominant. Judgements about a building’s congruity varied by up to 13% and buildings that featured harmonious colours were considered to be more congruous. Preference varied and harmonious façade colours were not necessarily preferred over contrasting façade colours. The outcomes from this research suggest that a new approach to façade colour within the context of planning policy may be appropriate. A model of façade colour evaluation is presented and, unlike current planning guidelines, the model allows for a participatory approach to façade colour evaluation and specification. The model allows for factors that may influence aesthetic response to façade colour (such as contextual, perceptual and idiographic factors) as well as variation in architectural expression with respect to façade colour

Investigating the Effect of Color Gamut Mapping Quantitatively and Visually

With the advent of various color management standards and tools, the print media industry has seen many advancements aimed towards quantitatively and qualitatively acceptable color reproduction. This research attempts to test one of the most fundamental and integral parts of a standard color management workflow, the profile. The gamut mapping techniques implemented by the ICC profiles created using different profiling application programs were tested for their congruity to the theoretical concepts, standards, and definitions documented by International Color Consortium (ICC). Once these profiling software applications were examined, the significance of the possible discrepancies were tested by establishing a visual assessment of pictorial images using these profiles. In short, this research assessed the implementations of the ICC color rendering intents in a standard or a commonly used color managed workflow, and then described the significance of these discrepancies in terms of interoperability. For this research, interoperability was defined the assessment of different ICC profiles in producing similar results, i.e., quantitatively and visually. In order to achieve the desired assessment, the two profiling applications were selected and each used to create an output profile using the same characterization data set. The two profiles were then compared for differences in the way they mapped real world colors. The results displayed that even though there were some significant quantitative color differences, visual subjective evaluation did not reflect any noticeable color differences and therefore concluded that the profiles were interoperable. These findings reveal that even though quantitative color differences may reflect significant color differences, subjective visual comparisons may not always reflect the same or agree with quantitative findings

Imaging methods for understanding and improving visual training in the geosciences

Experience in the field is a critical educational component of every student studying geology. However, it is typically difficult to ensure that every student gets the necessary experience because of monetary and scheduling limitations. Thus, we proposed to create a virtual field trip based off of an existing 10-day field trip to California taken as part of an undergraduate geology course at the University of Rochester. To assess the effectiveness of this approach, we also proposed to analyze the learning and observation processes of both students and experts during the real and virtual field trips. At sites intended for inclusion in the virtual field trip, we captured gigapixel resolution panoramas by taking hundreds of images using custom built robotic imaging systems. We gathered data to analyze the learning process by fitting each geology student and expert with a portable eye- tracking system that records a video of their eye movements and a video of the scene they are observing. An important component of analyzing the eye-tracking data requires mapping the gaze of each observer into a common reference frame. We have made progress towards developing a software tool that helps automate this procedure by using image feature tracking and registration methods to map the scene video frames from each eye-tracker onto a reference panorama for each site. For the purpose of creating a virtual field trip, we have a large scale semi-immersive display system that consists of four tiled projectors, which have been colorimetrically and photometrically calibrated, and a curved widescreen display surface. We use this system to present the previously captured panoramas, which simulates the experience of visiting the sites in person. In terms of broader geology education and outreach, we have created an interactive website that uses Google Earth as the interface for visually exploring the panoramas captured for each site

Spectral methods for multimodal data analysis

Spectral methods have proven themselves as an important and versatile tool in a wide range of problems in the fields of computer graphics, machine learning, pattern recognition, and computer vision, where many important problems boil down to constructing a Laplacian operator and finding a few of its eigenvalues and eigenfunctions. Classical examples include the computation of diffusion distances on manifolds in computer graphics, Laplacian eigenmaps, and spectral clustering in machine learning. In many cases, one has to deal with multiple data spaces simultaneously. For example, clustering multimedia data in machine learning applications involves various modalities or ``views'' (e.g., text and images), and finding correspondence between shapes in computer graphics problems is an operation performed between two or more modalities. In this thesis, we develop a generalization of spectral methods to deal with multiple data spaces and apply them to problems from the domains of computer graphics, machine learning, and image processing. Our main construction is based on simultaneous diagonalization of Laplacian operators. We present an efficient numerical technique for computing joint approximate eigenvectors of two or more Laplacians in challenging noisy scenarios, which also appears to be the first general non-smooth manifold optimization method. Finally, we use the relation between joint approximate diagonalizability and approximate commutativity of operators to define a structural similarity measure for images. We use this measure to perform structure-preserving color manipulations of a given image