abstract: This study examines the applicability of high dynamic range (HDR) imagery as a diagnostic tool for studying lighting quality in interior environments. It originates from the limitations in lighting quality assessments, particularly from the problematic nature of measuring luminance contrast--a significant lighting quality definer. In this research, HDR imaging method is studied systematically and in detail via extensive camera calibration tests considering the effect of lens and light source geometry (i.e. vignetting, point spread and modulation transfer functions), in-camera variables (i.e. spectral response, sensor sensitivity, metering mode,), and environmental variables (i.e. ambient light level, surface color and reflectance, light source spectral power distribution) on the accuracy of HDR-image-derived luminance data. The calibration test findings are used to create camera setup and calibration guidelines for future research, especially to help minimize errors in image extracted lighting data. The findings are also utilized to demonstrate the viability of the tool in a real world setting--an office environment combining vertical and horizontal tasks. Via the quasi-experimental setup, the relationship between line of sight and perceived luminance contrast ratios are studied using HDR images. Future research can benefit from the calibration guidelines to minimize HDR-based luminance estimation errors. The proposed tool can be used and tested in different contexts and tasks with varying user groups for revising the former luminance-contrast guidelines as well as surface reflectance recommendations. / Dissertation/Thesis / Ph.D. Architecture 2011

abstract: Super-Resolution (SR) techniques are widely developed to increase image resolution by fusing several Low-Resolution (LR) images of the same scene to overcome sensor hardware limitations and reduce media impairments in a cost-effective manner. When choosing a solution for the SR problem, there is always a trade-off between computational efficiency and High-Resolution (HR) image quality. Existing SR approaches suffer from extremely high computational requirements due to the high number of unknowns to be estimated in the solution of the SR inverse problem. This thesis proposes efficient iterative SR techniques based on Visual Attention (VA) and perceptual modeling of the human visual system. In the first part of this thesis, an efficient ATtentive-SELective Perceptual-based (AT-SELP) SR framework is presented, where only a subset of perceptually significant active pixels is selected for processing by the SR algorithm based on a local contrast sensitivity threshold model and a proposed low complexity saliency detector. The proposed saliency detector utilizes a probability of detection rule inspired by concepts of luminance masking and visual attention. The second part of this thesis further enhances on the efficiency of selective SR approaches by presenting an ATtentive (AT) SR framework that is completely driven by VA region detectors. Additionally, different VA techniques that combine several low-level features, such as center-surround differences in intensity and orientation, patch luminance and contrast, bandpass outputs of patch luminance and contrast, and difference of Gaussians of luminance intensity are integrated and analyzed to illustrate the effectiveness of the proposed selective SR frameworks. The proposed AT-SELP SR and AT-SR frameworks proved to be flexible by integrating a Maximum A Posteriori (MAP)-based SR algorithm as well as a fast two-stage Fusion-Restoration (FR) SR estimator. By adopting the proposed selective SR frameworks, simulation results show significant reduction on average in computational complexity with comparable visual quality in terms of quantitative metrics such as PSNR, SNR or MAE gains, and subjective assessment. The third part of this thesis proposes a Perceptually Weighted (WP) SR technique that incorporates unequal weighting parameters in the cost function of iterative SR problems. The proposed approach is inspired by the unequal processing of the Human Visual System (HVS) to different local image features in an image. Simulation results show an enhanced reconstruction quality and faster convergence rates when applied to the MAP-based and FR-based SR schemes. / Dissertation/Thesis / Ph.D. Electrical Engineering 2011

La simulation d'éclairage est un processus qui s'avère plus complexe (temps de calcul, coût mémoire, mise en œuvre complexe) aussi bien pour les matériaux brillants que pour les matériaux lambertiens ou spéculaires. Afin d'éviter le calcul coûteux de certains termes de l'équation de luminance (convolution entre la fonction de réflexion des matériaux et la distribution de luminance de l'environnement), nous proposons une nouvelle structure de données appelée Source Surfacique Équivalente (SSE). L'utilisation de cette structure de données nécessite le pré-calcul puis la modélisation du comportement des matériaux soumis à divers types de sources lumineuses (positions, étendues). L'exploitation d'algorithmes génétiques nous permet de déterminer les paramètres des modèles de BRDF, en introduisant une première source d'approximation. L'approche de simulation d'éclairage utilisée est basée sur un cache de luminance. Ce dernier consiste à stocker l'éclairement incident sous forme de SSE en des points appelés enregistrements. Durant la simulation d'éclairage, l'environnement lumineux doit également être assimilé à un ensemble de sources surfaciques équivalentes (en chaque enregistrement) qu'il convient de définir de manière dynamique. Cette phase constitue une deuxième source d'erreur. Toutefois, l'incertitude globale ne se réduit pas au cumul des approximations réalisées à chaque étape. Les comparatives réalisées prouvent, au contraire, que l'approche des Sources Surfaciques Équivalentes est particulièrement intéressante pour des matériaux rugueux ou pour les matériaux très brillants placés dans des environnements relativement uniformes. L'utilisation de SSE a permis de réduire considérablement à la fois le coût mémoire et le temps de calcul. Une fois que les SSE sont calculés en chaque enregistrement et pour un certain nombre de points de vue, nous proposons une nouvelle méthode de visualisation interactive exploitant les performances des GPU (carte graphique) et s'avérant plus rapide que les méthodes existantes. Enfin nous traiterons le cas où les grandeurs photométriques sont spectrales, ce qui est très important lorsqu'il s'agit de réaliser des simulations d'éclairage précises. Nous montrerons comment adapter les zones d'influence des enregistrements en fonction des gradients de luminance et de la géométrie autour des enregistrements. / Radiance caching methods have proven efficient for global illumination. Their goal is to compute precisely illumination values (incident radiance or irradiance) at a reasonable number of points lying on the scene surfaces. These points, called records, are stored in a cache used for estimating illumination of other points in the scene. Unfortunately, with records lying on glossy surfaces, the irradiance value alone is not sufficient to evaluate the reflected radiance; each record should also store the incident radiance for all incident directions. Memory storage can be reduced with projection techniques using spherical harmonics or other basis functions. These techniques provide good results with low shininess BRDFs. However, they get impractical for shininess of even moderate value since the number of projection coefficients increase drastically. In this paper, we propose a new radiance caching method, that handles highly glossy surfaces, while requiring a low memory storage. Each cache record stores a coarse representation of the incident illumination thanks to a new data structure called Equivalent Area light Sources (EAS), capable of handling fuzzy mirror surfaces. In addition, our method proposes a new simplification of the interpolation process since it avoids the need for expressing and evaluating complex gradients. Moreover, we propose a new GPU based visualisation method which exploits these EAS data structure. Thus, interactive rendering is done faster than existing methods. Finally, physical ligting simulations need to manipulate spectral physical quantities. We demonstrate in our work how these quantities can be handle with our technic by adapting the record influence zone depending on the radiance gradients and the geometry around the records.

Diploma thesis displaying black and white image in false color includes a study of methods and creation of computer software. The main function of the program is to convert the monochrome image into the pseudo colors. This procedure is achieved increasing the diagnostic yield of image. The program may find application in medical field. The pseudocoloring is used several different methods for obtaining the best results, combined with modifications increasing brightness scale image contrast images. The program is created in the programming environment of Visual Studio 2008 and written in C # programming language. Entry program is monochrome images in various formats (JPEG, BMP). The output of the program can be printed in a false-color image or stored image again in several different formats.

Artificial lighting is an integral part of our everyday life. Nowadays, a large number of people spend practically all their productive time in the presence of the artificial lighting system. This places considerable demands on the quality of this artificial lighting system. One of the indicators of the quality of the lighting system is the evaluation of glare. The UGR evaluation methodology is currently used to evaluate glare. However, the UGR rating has its limitations. These limitations include ambiguous assessments of luminaires with non-uniform luminous surface (so - called non - uniform luminaires). This diploma thesis deals with the issue of discomfort glare of non-uniform luminaires. The aim is to make a literature review of this issue. The first part focuses on theoretical knowledge of glare and its evaluation. Another part is an analysis of recent studies on the topic about glare from non-uniform types of luminaires. The last chapters of the thesis deal with own practical evaluation of glare.

The human visual system is tasked with transforming variations in light within our environment into a coherent percept, typically described using properties such as luminance and contrast. The experiments described in this dissertation examine how the human visual cortex responds to each of these stimulus properties at the population-level, and explores the degree to which contrast adaptation can alter these response properties. The first set of experiments (Chapter 2) demonstrate how saturating sigmoidal contrast response functions can be captured using human fMRI by leveraging sustained contrast adaptation to reduce the heterogeneity of response profiles across neural populations. The results obtained using this methodology have the potential to rectify the qualitatively different findings reported across visual neuroscience, when comparing electrophysiological and population-based neuroimaging measures. The second set of experiments (Chapter 3) demonstrate how under certain conditions a well-established visuocortical response property, contrast response, can also reflect luminance encoding, challenging the idea that luminance information plays no significant role in supporting visual perception. Specifically, these results show that the mean luminance information of a visual signal persists within visuocortical representations, even after controlling for pupillary dynamics, and potentially reflects an inherent imbalance of excitatory and inhibitory components. The final set of experiments (Chapter 4) examine how the time course of population activity during initial periods of adaptation differs across seemingly slightly different adapter conditions. The degree to which stimulus adapter orientation bias (radial vs. concentric orientation) or stimulus adapter luminance (2409 cd/m2 vs. 757.3 cd/m2) can alter adaptation time course dynamics is examined in detail, as well as investigating the prevalence of any retinotopic bias. In an effort to coalesce the findings across all three chapters, the shape and efficacy of the initial adaptation time course is ultimately compared against the contrast and luminance response function parameters reported in previous chapters. As a whole, the findings reported in this dissertation challenge some common assumptions about how the early human visual cortex adjusts and responds to the environment, provide methodological tools and stimulus design caveats vision neuroscientists will need to consider, and play a significant role in cortical models of vision.

No description available.

The aim of the present study was to characterize participants’ abilities to answer binary yes/no questions by mentally manipulating imagery to produce imagined changes in luminance, which would in turn cause reflexive perturbations in pupil diameter. First, a paired association was established with participants, linking “yes” responses with imagining a “sunny sky” and “no” responses with imagining a “dark room”. Participants (N=20) then answered 16 yes/no questions using this response method, in place of providing verbal or gestural (e.g., head nod) answers. Pupil diameters were recorded for a period of 8000 ms following each stimulus question while participants maintained the mental image that corresponded with their answer. We hypothesized that on average, “no” responses would yield a pupil dilation and increased diameter relative to baseline, while “yes” responses would instead result in constrictions and smaller pupil diameters compared to baseline. A 2-factor repeated measures analysis of variance (ANOVA), where time was one factor and response type (i.e., yes or no) was the other, revealed a statistically significant interaction of time and response type, a significant main effect of time, and a trend toward significance for response type in aggregated group data. Item level discrimination consisted of comparing the mean pupil diameter in response to a single item for a single participant (e.g., “yes” response on one trial) to the mean pupil diameter of all contrasting responses for that same participant (e.g., all “no” response trials). This method achieved a 64.5% discrimination accuracy. This investigation affirmed the plausibility of leveraging pupillometry and luminance-based mental imagery in favor of an alternative communication system for individuals who are locked-in, as well as its potential as a screening tool. However, further investigation is warranted prior to its implementation. / Communication Sciences

This study compared two LED luminaires and their abilities to provide detection distance and color recognition distance of potential roadway hazard. Detection distance is regarded as a metric of visibility. Color recognition distance is a metric for comparing the impact of the (Correlated Color Temperature) CCT of each luminaire and their color contrast impact. Mesopic vision, the mode of vision most commonly used for night driving, was considered in this study. Off-axis objects were presented to participants to assess the peripheral abilities of the luminaires. The impacts of luminance and color contrast were addressed in this study. The experiment was performed on the Virginia Smart Road where standard objects of different colors and pedestrians wearing different colors were detected by drivers of a moving vehicle in a controlled environment. The key difference between the two luminaires was their color temperatures (3500K versus 6000K). The results indicated that neither light source provided a significant benefit over the other although significant interactions were found among object color, age, and lighting level. The results indicate that the luminaires provide similar luminance contrast but their color contrasts depend heavily on the color temperature, the object, and the observer. This study followed the protocol developed by the Mesopic Optimisation of Visual Efficiency (MOVE) consortium developed by the CIE for modeling mesopic visual behavior. / Master of Science

Les personnes ayant un trouble du spectre autistique (TSA) manifestent des particularités perceptives. En vision, des travaux influents chez les adultes ont mené à l’élaboration d’un modèle explicatif du fonctionnement perceptif autistique qui suggère que l’efficacité du traitement visuel varie en fonction de la complexité des réseaux neuronaux impliqués (Hypothèse spécifique à la complexité). Ainsi, lorsque plusieurs aires corticales sont recrutées pour traiter un stimulus complexe (e.g., modulations de texture; attributs de deuxième ordre), les adultes autistes démontrent une sensibilité diminuée. À l’inverse, lorsque le traitement repose principalement sur le cortex visuel primaire V1 (e.g., modulations locales de luminance; attributs de premier ordre), leur sensibilité est augmentée (matériel statique) ou intacte (matériel dynamique). Cette dissociation de performance est spécifique aux TSA et peut s’expliquer, entre autre, par une connectivité atypique au sein de leur cortex visuel. Les mécanismes neuronaux précis demeurent néanmoins méconnus. De plus, on ignore si cette signature perceptuelle est présente à l’enfance, information cruciale pour les théories perceptives de l’autisme. Le premier volet de cette thèse cherche à vérifier, à l’aide de la psychophysique et l’électrophysiologie, si la double dissociation de performance entre les attributs statiques de premier et deuxième ordre se retrouve également chez les enfants autistes d’âge scolaire. Le second volet vise à évaluer chez les enfants autistes l’intégrité des connexions visuelles descendantes impliquées dans le traitement des textures. À cet effet, une composante électrophysiologique reflétant principalement des processus de rétroaction corticale a été obtenue lors d’une tâche de ségrégation des textures. Les résultats comportementaux obtenus à l’étude 1 révèlent des seuils sensoriels similaires entre les enfants typiques et autistes à l’égard des stimuli définis par des variations de luminance et de texture. Quant aux données électrophysiologiques, il n’y a pas de différence de groupe en ce qui concerne le traitement cérébral associé aux stimuli définis par des variations de luminance. Cependant, contrairement aux enfants typiques, les enfants autistes ne démontrent pas une augmentation systématique d’activité cérébrale en réponse aux stimuli définis par des variations de texture pendant les fenêtres temporelles préférentiellement associées au traitement de deuxième ordre. Ces différences d’activation émergent après 200 ms et engagent les aires visuelles extrastriées des régions occipito-temporales et pariétales. Concernant la connectivité cérébrale, l’étude 2 indique que les connexions visuelles descendantes sont fortement asymétriques chez les enfants autistes, en défaveur de la région occipito-temporale droite. Ceci diffère des enfants typiques pour qui le signal électrophysiologique reflétant l’intégration visuo-corticale est similaire entre l’hémisphère gauche et droit du cerveau. En somme, en accord avec l’hypothèse spécifique à la complexité, la représentation corticale du traitement de deuxième ordre (texture) est atypiquement diminuée chez les enfants autistes, et un des mécanismes cérébraux impliqués est une altération des processus de rétroaction visuelle entre les aires visuelles de haut et bas niveau. En revanche, contrairement aux résultats obtenus chez les adultes, il n’y a aucun indice qui laisse suggérer la présence de mécanismes supérieurs pour le traitement de premier ordre (luminance) chez les enfants autistes. / Atypical perceptual information processing is commonly described in Autism Spectrum Disorders (ASD). In the visual modality, influential work with autistic adults suggests altered connectivity within specialized local networks defining the response properties of stimulus-driven mechanisms. This has led to the development of a hypothesis that stipulates that the efficiency of autistic visual perception is contingent on the complexity of the neural network involved (Complexity-specific hypothesis). When several cortical areas must communicate with each other (as in texture-defined perception, also called second-order), reduced sensitivity to visual input is observed in autistic individuals. In contrast, when visual processing predominately relies on the primary visual cortex V1 (as in luminance-defined perception, also called first-order), their sensitivity is either enhanced (stationary stimuli) or intact (moving stimuli). This dissociation in performance is unique to ASD and suggests atypical connectivity within their visual cortex. The precise type of neural alteration remains unknown, however. In addition, studies focusing on younger individuals are needed to define the developmental trajectories of perceptual abilities in autism. This issue is crucial for perceptual theories of ASD. The first experiment aims to investigate whether the dissociation regarding first- and second-order spatial vision is also present in school-aged children with autism. We combined the use of behavioural (psychophysics) and neuroimaging (visual evoked potentials: VEPs) methods. The second experiment was designed to assess the integrity of one type of neural connections that are known to be involved in texture processing: feedback processes from extrastriate areas towards lower hierarchical levels (V1). As such, we used a visual texture segregation task and isolated a texture-segregation specific VEP component that mainly reflects feedback modulation in the visual cortex. Behavioural measures from the first experiment do not reveal differences in visual thresholds between typically developing and autistic children for both luminance- and texture-defined stimuli. With respect to electrophysiology, there is no group difference in brain activity associated with luminance-defined stimuli. However, unlike typical children, autistic children do not reliably show reliable enhancements of brain activity in response to texture-defined stimuli during time-windows more closely associated with second-order processing. These differences emerge after 200 msec post-stimulation and mainly involve extrastriate areas located over occipito-temporal and parietal scalp areas. Regarding the second experiment, the texture-segregation specific VEP component is found to be greatly diminished over the right as compared to the left occipito-lateral cortex in autism, while it shows no hemispheric asymmetry in typically developing children. In summary, in line with the complexity-specific hypothesis, cortical representation of second-order attributes (texture) is atypically reduced in autistic children. This thesis further reveals that altered feedback from extrastriate visual areas to lower areas (V1) is one of the neuronal mechanisms involved in atypical texture processing. In contrast, contrary to the results obtained in adults with autism, first-order vision (luminance) is not found to be superior in autistic children.