Humans distinguish materials such as metal, plastic, and paper effortlessly at a glance. Traditional computer vision systems cannot solve this problem at all. Recognizing surface reflectance properties from a single photograph is difficult because the observed image depends heavily on the amount of light incident from every direction. A mirrored sphere, for example, produces a different image in every environment. To make matters worse, two surfaces with different reflectance properties could produce identical images. The mirrored sphere simply reflects its surroundings, so in the right artificial setting, it could mimic the appearance of a matte ping-pong ball. Yet, humans possess an intuitive sense of what materials typically "look like" in the real world. This thesis develops computational algorithms with a similar ability to recognize reflectance properties from photographs under unknown, real-world illumination conditions. Real-world illumination is complex, with light typically incident on a surface from every direction. We find, however, that real-world illumination patterns are not arbitrary. They exhibit highly predictable spatial structure, which we describe largely in the wavelet domain. Although they differ in several respects from the typical photographs, illumination patterns share much of the regularity described in the natural image statistics literature. These properties of real-world illumination lead to predictable image statistics for a surface with given reflectance properties. We construct a system that classifies a surface according to its reflectance from a single photograph under unknown illuminination. Our algorithm learns relationships between surface reflectance and certain statistics computed from the observed image. Like the human visual system, we solve the otherwise underconstrained inverse problem of reflectance estimation by taking advantage of the statistical regularity of illumination. For surfaces with homogeneous reflectance properties and known geometry, our system rivals human performance.

This thesis analyzes the reflectance behavior of textiles in the short-wave infrared (SWIR) band (1 – 2 microns) in order to identify/design potential diagnostic tools that allow the remote detection of human presence in a scene. Analyzing the spectral response of fabrics in the SWIR band has gained significant interest in the remote sensing community since it provides a potential path to discriminate camouflaged clothing from backgrounds that appear similar to the object of interest in the visible band. Existing research, originating primarily from the textiles community, has thoroughly documented the behavior of clothing fabrics in the visible band. Other work has shown that the differences in spectral response in the SWIR band allows for discrimination of materials that otherwise have the same visible spectral response. This work expands on those efforts in order to quantify the reflectance behavior and to better understand the physical basis for that behavior.

Creating realistic-looking skin is one of the holy grails of computer graphics and is still an active area of research. The problem is challenging due to the inherent complexity of skin and its variations, not only across individuals but also spatially and temporally among one. Skin appearance and reflectance vary spatially in one individual depending on its location on the human body, but also vary temporally with the aging process and the body state. Emotions, health, physical activity, and cosmetics for example can all affect the appearance of skin. The spatially varying reflectance of skin is due to many parameters, such as skin micro- and meso-geometry, thickness, oiliness, and pigmentation. It is therefore a daunting task to derive a model that will include all these parameters to produce realistic-looking skin. The problem is also compounded by the fact that we are very well accustomed to the appearance of skin and especially sensitive to facial appearances and expressions. Skin modelling and rendering is crucial for many applications such as games, virtual reality, films, and the beauty industry, to name a few. Realistic-looking skin improves the believability and realism of applications. The complexity of skin makes the topic of skin modelling and rendering for computer graphics a very difficult, but highly stimulating one. Skin deformations and biomechanics is a vast topic that we will not address in this dissertation. We rather focus our attention on skin optics and present a simple model for the reflectance of human skin along with a system to support skin modelling and rendering.

The bidirectional reflectance distribution function has a four dimensional parameter space and such high dimensionality makes it impractical to use it directly in hardware rendering. When a BRDF has no analytical representation, common solutions to overcome this problem include expressing it as a sum of basis functions or factorizing it into several functions of smaller dimensions. This thesis describes factorization extensions that significantly improve factor computation speed and eliminate drawbacks of previous techniques that overemphasize low sample values. The improved algorithm is used to calculate factorizations and material maps from colored images. The technique presented in this thesis allows interactive definition of arbitrary materials, and although this method is based on physical parameters, it can be also used for achieving a variety of non-photorealistic effects.

<p>Variations in hemoglobin concentration can be indicative of a number of serious complications, including blood loss and anemia. Rapid, noninvasive measurements of hemoglobin are important in applications where blood status is reflective of patient well-being, such as in the emergency room, operating room, or the battlefield. Probe-based diffuse reflectance spectroscopy is capable of noninvasively quantifying tissue optical properties, including hemoglobin concentration. The quantification of hemoglobin concentration using optical methods is complicated by tissue scattering and the robustness of the algorithm and instrumentation used to interrogate the tissue. The sensing depth of diffuse reflectance spectroscopy can be tailored by the wavelengths of light and probe design used.</p><p>In this thesis, the accuracy and clinical viability of different diffuse reflectance spectroscopy implementations are presented. The robustness of an inverse Monte Carlo model, in which tissue optical properties are determined from measured reflectance using ultraviolet-visible (UV-VIS) wavelengths and a steady-state instrument, was tested using laboratory measurements. From the laboratory measurements, a set of references was identified which provided accurate absorption and scattering measurements, independent of the optical properties of the target. In addition, the ability to quantify hemoglobin concentration and saturation over large ranges and concentrations of multiple absorbers was established. </p><p>Following the laboratory measurements, a clinical study in which UV-VIS spectra were measured from the sublingual mucosa of patients undergoing surgeries was carried out. From this study, the correlations of extracted hemoglobin to expected blood hemoglobin were found to be improved when a simple ratiometric method based on isosbestic wavelengths of hemoglobin was used. During this study, the probe positioning in the mouth was found to be unwieldy, and so the transition to a more secure probe that could be taped to the hand was made. </p><p>In order to penetrate the overlying skin, near-infrared (NIR) wavelengths with a different probe geometry was explored. Further investigation of the inverse Monte Carlo model with NIR wavelengths was executed, and while in theory this combination should yield accurate optical property estimation, laboratory measurements indicated large errors, presumably due to the instrument or low magnitude and reduced spectral features of hemoglobin absorption in the NIR. Instead, the use of a well-established frequency-domain instrument coupled with diffusion approximation was implemented to measure spectra from the thenar eminence of volunteers undergoing induced hypovolemia and subsequent retransfusion. There were some moderate correlations with blood hemoglobin, but because both this method and the Monte Carlo method with mucosal probe placement showed higher variability with probe pressure than the isosbestic ratiometric method, further development of the ratiometric method was made. </p><p>The ratiometric method was developed using simulations and validated with phantoms and clinical data. Monte Carlo modeled reflectance was generated for a large range of biologically-relevant absorption and scattering values. The modeled reflectance was scaled by a calibration spectra obtained from a single laboratory phantom measurement so that linear regression equations relating hemoglobin concentration to ratios could be applied directly to clinical or laboratory measurements. Ratios which could best estimate hemoglobin concentration independent of saturation and scattering were determined through the simulation and laboratory measurements. Three isosbestic ratios - 545/390, 452/390, and 529/390 nm - were determined to best estimate hemoglobin concentration, and ratiometric-extracted hemoglobin was shown to correlate well to Monte Carlo-extracted hemoglobin in clinical measurements. Because only a single calibration measurement (which can be measured on a different day) is required per instrument and probe combination, this method can be implemented in near real-time and is thus appropriate for applications where hemoglobin concentration must be measured rapidly.</p> / Dissertation

This paper study the influence of surface properties of encapsulated CLC on response time and reflectance via polymerization induced phase separation. The cured polymer layer, which is composed of the mixture of EMA and TRI, adhere to the inside of the non-treated glass substrate and change the surface properties to vertical alignments. Different boundary conditions caused by various UV curing intensity and cell gap lead to different electro-optical properties for CLC display. With a proper boundary structure, the transition time from homeotropic to planar of CLC can be reduced obviously with slightly reduced reflectance.

Cool roofs are the roofs that can deliver high solar reflectance and high thermal emittance. The benefits associated with cool roofs include reduced cooling energy load, reduced air pollution and greenhouse gas emission, and improved human health and comfort. This study attempts to develop standard measurement method for evaluating the reflectance and emmittance of a cool roof material. First, a literature survey was conducted to analysis the current programs promoting the use of cool roofs in the world, and then more than 2000 cool roof materials¡¦ data were collected in this study. In addition, the dynamic building energy load simulation by using eQuest was conducted to investigate the energy-saving benefits of cool roof applied in Taiwan. The results indicated that the reflectance, emmittance and thermal conductivity have a significant effect on the roof heat gain. The higher reflectance or emmittance of the roof, the less heat gain absorbed in the roof. But, reflectance has a larger effect on roof energy-saving than emittance does. The energy-saving effect by using cool roof on the flat-type roof is larger than on low-slope type roof.

Thesis (M.S.)--Worcester Polytechnic Institute. / Keywords: scene reconstruction vision, image based rendering, graphics, color consistency, specular objects. Includes bibliographical references (p. 56-57).

This dissertation focuses on the development of computational models and algorithms related to diffuse reflectance spectroscopy. Specifically, this work aims to advance diffuse reflectance spectroscopy to a technique that is capable of measuring depth dependent properties in tissue. First, we introduce the Monte Carlo lookup table (MCLUT) method for extracting optical properties from diffuse reflectance spectra. Next, we extend this method to a two-layer tissue geometry so that it can extract depth dependent properties in tissue. We then develop a computational model that relates photon sampling depth to optical properties and probe geometry. This model can be used to aid in design of application specific diffuse reflectance probes. In order to provide justification for using a two-layer model for extracting tissue properties, we show that the use of a one-layer model can lead to significant errors in the extracted optical properties. Lastly, we use our two-layer MCLUT model and a probe that was designed based on our sampling depth model to extract tissue properties from the skin of 80 subjects at 5 anatomical locations. The results agree with previously published values for skin properties and show that can diffuse reflectance spectroscopy can be used to measured depth dependent properties in tissue. / text

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