Motion of glossy objects does not promote separation of lighting and surface colour

The surface properties of an object, such as texture, glossiness or colour, provide important cues to its identity. However, the actual visual stimulus received by the eye is determined by both the properties of the object and the illumination. We tested whether operational colour constancy for glossy objects (the ability to distinguish changes in spectral reflectance of the object, from changes in the spectrum of the illumination) was affected by rotational motion of either the object or the light source. The different chromatic and geometric properties of the specular and diffuse reflections provide the basis for this discrimination, and we systematically varied specularity to control the available information. Observers viewed animations of isolated objects undergoing either lighting or surface-based spectral transformations accompanied by motion. By varying the axis of rotation, and surface patterning or geometry, we manipulated: (i) motion-related information about the scene, (ii) relative motion between the surface patterning and the specular reflection of the lighting, and (iii) image disruption caused by this motion. Despite large individual differences in performance with static stimuli, motion manipulations neither improved nor degraded performance. As motion significantly disrupts frameby-frame low-level image statistics, we infer that operational constancy depends on a high-level scene interpretation, which is maintained in all condition

Determinants of colour constancy

Colour constancy describes the ability of our visual system to keep colour percepts stable through illumination changes. This is an outstanding feat given that in the retinal image surface and illuminant properties are conflated. Still, in our everyday lives we are able attribute stable colour-labels to objects to make communication economic and efficient. Past research shows colour constancy to be imperfect, compensating for 40% and 80% of the illumination change. While different constancy determinants are suggested, no carefully controlled study shows perfect constancy. The first study presented here addresses the issue of imperfect constancy by investigating colour constancy in a cue rich environment, using a task that resembles our everyday experience with colours. Participants were asked to recall the colour of unique personal objects in natural environment under four chromatic illuminations. This approach yielded perfect colour constancy. The second study investigated the relation between illumination discrimination and chromatic detection. Recent studies using an illumination discrimination paradigm suggest that colour constancy is optimized for bluish daylight illuminations. Because it is not clear if illumination discrimination is directly related to colour constancy or is instead explained by sensitivity to changes in chromaticity of different hues, thresholds for illumination discrimination and chromatic detection for the same 12 illumination hues were compared. While the reported blue bias could be replicated, thresholds for illumination discrimination and chromatic detection were highly related, indicating that lower sensibility towards bluish hues is not exclusive to illumination discrimination. Accompanying the second study, the third study investigated the distribution of colour constancy for 40 chromatic illuminations of different hue using achromatic adjustments and colour naming. These measurements were compared to several determinants of colour constancy, including the daylight locus, colour categories, illumination discrimination, chromatic detection, relational colour constancy and metameric mismatching. In accordance with the observations in study 2, achromatic adjustments revealed a bias towards bluish daylight illumination. This blue bias and naming consistency explained most of the variance in achromatic adjustments, while illumination discrimination was not directly related to colour constancy. The fourth study examined colour memory biases. Past research shows that colours of objects are remembered as being more saturated than they are perceived. These works often used natural objects that exist in a variety of colour and hue, such as grass or bananas. The approach presented here directly compared perceived and memorized colours for unique objects, used also in the first study, and confirmed the previous findings that on average, objects were remembered more saturated than they were perceived.Farbkonstanz beschreibt die Fähigkeit unseres visuellen Systems Farbeindrücke unter Beleuchtungsänderungen beständig zu halten. Dies ist eine außergewöhnliche Leistung, wenn man in Betracht zieht, dass in dem Lichtsignal welches das Auge erreicht Eigenschaften der Beleuchtung und der Oberflächen konfundiert sind. Trotz dieser Problematik sind wir in unserem alltäglichen Leben in der Lage Objekten stabile Farbnamen zuzuordnen, und damit unsere Kommunikation effizient und ökonomisch zu gestalten. Bisherige Studien zur Farbkonstanz berichten jedoch, dass Farbkonstanz nicht perfekt ist, Beleuchtungswechsel wurden nur zwischen 40-80% kompensiert. Während unterschiedliche Determinanten der Farbkonstanz vorgeschlagen wurden, konnte bisher keine sorgfältig kontrollierte Studie perfekte Farbkonstanz zeigen. In der ersten Studie dieser Arbeit wurde dieser Aspekt untersucht, indem Farbkonstanz in einer hinweisreichen Umgebung unter Verwendung einer Aufgabe, die möglichst präzise unserer alltäglichen Erfahrung im Umgang mit Farben wiederspiegelt, gemessen wurde. Die Versuchsteilnehmer wurden aufgefordert die Farbe eines spezifischen persönlichen Gegenstandes unter vier farbigen Beleuchtungen aus dem Gedächtnis abzurufen. Unter Verwendung dieses Ansatzes konnte perfekte Farbkonstanz erreicht werden. Die zweite Studie untersuchte die Beziehung zwischen Beleuchtungs-Diskrimination und chromatischer Detektion. Die Ergebnisse von kürzlich veröffentlichten Forschungsarbeiten, welche ein Beleuchtungs-Diskriminations-Paradigma verwendeten, zeigen das diese Diskrimination in Richtung bläulicher Beleuchtung verzerrt ist. Daraus wurde geschlossen, das Farbkonstanz für bläuliche Tageslicht-Beleuchtungen optimiert ist . Da es aber nicht klar ist, ob Beleuchtungs-Diskrimination in direkter Beziehung zur Farbkonstanz steht, oder aber vielmehr auf die Sensitivität für chromatische Veränderungen zurückführen ist, wurden Wahrnehmungsschwellen für Beleuchtungs-Diskrimination und chromatische Detektion für die selben 12 Beleuchtungsfarben gemessen und verglichen. Während die bereits berichtete Verzerrung in Richtung der bläulichen Tageslichtbeleuchtung repliziert werden konnte, wurde ebenfalls eine hoher Zusammenhang zwischen chromatischer Detektion und Beleuchtungs-Diskrimination gefunden, welcher darauf hinweist, dass die Verzerrung in Richtung bläulicher Farben keine exklusive Eigenschaft der Beleuchtung-Diskrimination ist. Anknüpfend an die zweite Studie wurde in der dritten Studie die Verteilung von Farbkonstanz über 40 chromatische Beleuchtungen anhand von achromatischen Einstellungen und Farbbenennung untersucht. Farbkonstanz wurde auf ihren Zusammenhang zu mehreren Determinanten der Farbkonstanz überprüft, unter anderem mit Tageslichtvariationen, Farbkategorien, Beleuchtungs-Diskrimination, relationaler Farbkonstanz und metameric mismatching. In Übereinstimmung mit der zweiten Studie wurde auch für achromatische Einstellungen eine Verzerrung in Richtung bläulicher Tageslichtbeleuchtungen gefunden. Diese Verzerrung und der Konsensus der Beleuchtungsbenennung erklärten den Großteil der Varianz der achromatischen Einstellungen, während Beleuchtungs-Diskrimination nicht in direkter Verbindung zur Farbkonstanz stand. In der vierten Studie wurden Verzerrungen des Farbgedächtnisses untersucht. Frühere Studien berichten, dass Objektfarben häufig gesättigter erinnert werden als sie tatsächlich wahrgenommen werden. In diesen Studien wurden häufig natürliche Objekte verwendet, die in einer Vielzahl an Farbtönen und Sättigungen existieren, wie beispielsweise Gras oder Bananen. In dem hier präsentierten Ansatz wurden Farbwahlen aus dem Gedächtnis mit Farbwahlen der direkten Objektwahrnehmung für persönliche, spezifische Objekte, die auch schon in der ersten Studie verwendet wurden, verglichen. Die Ergebnisse der vorherigen Studien konnten für diese Objekte repliziert werden: Im Durchschnitt wurden Objektfarben gesättigter erinnert als das Objekt im direkten Vergleich wahrgenommen wurde

Novel image enhancement technique using shunting inhibitory cellular neural networks

This paper describes a method for improving image quality in a color CMOS image sensor. The technique simultaneously acts to compress the dynamic range, reorganize the signal to improve visibility, suppress noise, identify local features, achieve color constancy, and lightness rendition. An efficient hardware architecture and a rigorous analysis of the different modules are presented to achieve high quality CMOS digital camera

The Computation of Surface Lightness in Simple and Complex Scenes

The present thesis examined how reflectance properties and the complexity of surface mesostructure (small-scale surface relief) influence perceived lightness in centresurround displays. Chapters 2 and 3 evaluated the role of surface relief, gloss, and interreflections on lightness constancy, which was examined across changes in background albedo and illumination level. For surfaces with visible mesostructure (“rocky” surfaces), lightness constancy across changes in background albedo was better for targets embedded in glossy versus matte surfaces. However, this improved lightness constancy for gloss was not observed when illumination varied. Control experiments compared the matte and glossy rocky surrounds to two control displays, which matched either pixel histograms or a phase-scrambled power spectrum. Lightness constancy was improved for rocky glossy displays over the histogram-matched displays, but not compared to phase-scrambled variants of these images with equated power spectrums. The results were similar for surfaces rendered with 1, 2, 3 and 4 interreflections. These results suggest that lightness perception in complex centre-surround displays can be explained by the distribution of contrast across space and scale, independently of explicit information about surface shading or specularity. The results for surfaces without surface relief (“homogeneous” surfaces) differed qualitatively to rocky surfaces, exhibiting abrupt steps in perceived lightness at points at which the targets transitioned from being increments to decrements. Chapter 4 examined whether homogeneous displays evoke more complex mid-level representations similar to conditions of transparency. Matching target lightness in a homogeneous display to that in a textured or rocky display required varying both lightness and transmittance of the test patch on the textured display to obtain the most satisfactory matches. However, transmittance was only varied to match the contrast of targets against homogeneous surrounds, and not to explicitly match the amount of transparency perceived in the displays. The results suggest perceived target-surround edge contrast differs between homogeneous and textured displays. Varying the mid-level property of transparency in textured displays provides a natural means for equating both target lightness and the unique appearance of the edge contrast in homogeneous displays

The Computation of Surface Lightness in Simple and Complex Scenes

The present thesis examined how reflectance properties and the complexity of surface mesostructure (small-scale surface relief) influence perceived lightness in centresurround displays. Chapters 2 and 3 evaluated the role of surface relief, gloss, and interreflections on lightness constancy, which was examined across changes in background albedo and illumination level. For surfaces with visible mesostructure (“rocky” surfaces), lightness constancy across changes in background albedo was better for targets embedded in glossy versus matte surfaces. However, this improved lightness constancy for gloss was not observed when illumination varied. Control experiments compared the matte and glossy rocky surrounds to two control displays, which matched either pixel histograms or a phase-scrambled power spectrum. Lightness constancy was improved for rocky glossy displays over the histogram-matched displays, but not compared to phase-scrambled variants of these images with equated power spectrums. The results were similar for surfaces rendered with 1, 2, 3 and 4 interreflections. These results suggest that lightness perception in complex centre-surround displays can be explained by the distribution of contrast across space and scale, independently of explicit information about surface shading or specularity. The results for surfaces without surface relief (“homogeneous” surfaces) differed qualitatively to rocky surfaces, exhibiting abrupt steps in perceived lightness at points at which the targets transitioned from being increments to decrements. Chapter 4 examined whether homogeneous displays evoke more complex mid-level representations similar to conditions of transparency. Matching target lightness in a homogeneous display to that in a textured or rocky display required varying both lightness and transmittance of the test patch on the textured display to obtain the most satisfactory matches. However, transmittance was only varied to match the contrast of targets against homogeneous surrounds, and not to explicitly match the amount of transparency perceived in the displays. The results suggest perceived target-surround edge contrast differs between homogeneous and textured displays. Varying the mid-level property of transparency in textured displays provides a natural means for equating both target lightness and the unique appearance of the edge contrast in homogeneous displays

Computational mechanisms for colour and lightness constancy

Attributes of colour images have been found which allow colour and lightness constancy to be computed without prior knowledge of the illumination, even in complex scenes with three -dimensional objects and multiple light sources of different colours. The ratio of surface reflectance colour can be immediately determined between any two image points, however distant. It is possible to determine the number of spectrally independent light sources, and to isolate the effect of each. Reflectance edges across which the illumination remains constant can be correctly identified.In a scene illuminated by multiple distant point sources of distinguishalbe colours, the spatial angle between the sources and their brightness ratios can be computed from the image alone. If there are three or more sources then reflectance constancy is immediately possible without use of additional knowledge.The results are an extension of Edwin Land's Retinex algorithm. They account for previously unexplained data such as Gilchrist's veiling luminances and his single- colour rooms.The validity of the algorithms has been demonstrated by implementing them in a series of computer programs. The computational methods do not follow the edge or region finding paradigms of previous vision mechanisms. Although the new reflectance constancy cues occur in all normal scenes, it is likely that human vision makes use of only some of them.In a colour image all the pixels of a single surface colour lie in a single structure in flux space. The dimension of the structure equals the number of illumination colours. The reflectance ratio between two regions is determined by the transformation between their structures. Parallel tracing of edge pairs in their respective structures identifies an edge of constant illumination, and gives the lightness ratio of each such edge. Enhanced noise reduction techniques for colour pictures follow from the natural constraints on the flux structures

The Constructive Nature of Color Vision and Its Neural Basis

Our visual world is made up of colored surfaces. The color of a surface is physically determined by its reflectance, i.e., how much energy it reflects as a function of wavelength. Reflected light, however, provides only ambiguous information about the color of a surface as it depends on the spectral properties of both the surface and the illumination. Despite the confounding effects of illumination on the reflected light, the visual system is remarkably good at inferring the reflectance of a surface, enabling observers to perceive surface colors as stable across illumination changes. This capacity of the visual system is called color constancy and it highlights that color vision is a constructive process. The research presented here investigates the neural basis of some of the most relevant aspects of the constructive nature of human color vision using machine learning algorithms and functional neuroimaging. The experiments demonstrate that color-related prior knowledge influences neural signals already in the earliest area of visual processing in the cortex, area V1, whereas in object imagery, perceived color shared neural representations with the color of the imagined objects in human V4. A direct test for illumination-invariant surface color representation showed that neural coding in V1 as well as a region anterior to human V4 was robust against illumination changes. In sum, the present research shows how different aspects of the constructive nature of color vision can be mapped to different regions in the ventral visual pathway

Colour constancy "explained"

Smeets, J.B.J. [Promotor]Brenner, E.M. [Copromotor

Change blindness: eradication of gestalt strategies

Arrays of eight, texture-defined rectangles were used as stimuli in a one-shot change blindness (CB) task where there was a 50% chance that one rectangle would change orientation between two successive presentations separated by an interval. CB was eliminated by cueing the target rectangle in the first stimulus, reduced by cueing in the interval and unaffected by cueing in the second presentation. This supports the idea that a representation was formed that persisted through the interval before being 'overwritten' by the second presentation (Landman et al, 2003 Vision Research 43149–164]. Another possibility is that participants used some kind of grouping or Gestalt strategy. To test this we changed the spatial position of the rectangles in the second presentation by shifting them along imaginary spokes (by ±1 degree) emanating from the central fixation point. There was no significant difference seen in performance between this and the standard task [F(1,4)=2.565, p=0.185]. This may suggest two things: (i) Gestalt grouping is not used as a strategy in these tasks, and (ii) it gives further weight to the argument that objects may be stored and retrieved from a pre-attentional store during this task