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

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

Integration and Segregation in Audition and Vision

Perceptual systems can improve their performance by integrating relevant perceptual information and segregating away irrelevant information. Three studies exploring perceptual integration and segregation in audition and vision are reported in this thesis. In Chapter 1, we explore the role of similarity in informational masking. In informational masking tasks, listeners detect the presence of a signal tone presented simultaneously with a random-frequency multitone masker. Detection thresholds are high in the presence of an informational masker, even though listeners should be able to ignore the masker frequencies. The informational masker\u27s effect may be due to the similarity between signal and masker components. We used a behavioral measure to demonstrate that the amount of frequency change over time could be the stimulus dimension underlying the similarity effect. In Chapter 2, we report a set of experiments on the visual system\u27s ability to discriminate distributions of luminances. The distribution of luminances can serve as a cue to the presence of multiple illuminants in a scene. We presented observers with simple achromatic scenes with patches drawn from one or two luminance distributions. Performance depended on the number of patches from the second luminance distribution, as well as knowledge of the location of these patches. Irrelevant geometric cues, which we expected to negatively affect performance, did not have an effect. An ideal observer model and a classification analysis showed that observers successfully integrated information provided by the image photometric cues. In Chapter 3, we investigated the role of photometric and geometric cues in lightness perception. We rendered achromatic scenes that were consistent with two oriented background context surfaces illuminated by a light source with a directional component. Observers made lightness matches to tabs rendered at different orientations in the scene. We manipulated the photometric cues by changing the intensity of the illumination, and the geometric cues by changing the orientation of the context surfaces. Observers\u27 matches varied with both manipulations, demonstrating that observers used both types of cues to account for the illumination in the scene. The two types of cues were found to have independent effects on the lightness matches

Ridge Regression Approach to Color Constancy

This thesis presents the work on color constancy and its application in the field of computer vision. Color constancy is a phenomena of representing (visualizing) the reflectance properties of the scene independent of the illumination spectrum. The motivation behind this work is two folds:The primary motivation is to seek ‘consistency and stability’ in color reproduction and algorithm performance respectively because color is used as one of the important features in many computer vision applications; therefore consistency of the color features is essential for high application success. Second motivation is to reduce ‘computational complexity’ without sacrificing the primary motivation.This work presents machine learning approach to color constancy. An empirical model is developed from the training data. Neural network and support vector machine are two prominent nonlinear learning theories. The work on support vector machine based color constancy shows its superior performance over neural networks based color constancy in terms of stability. But support vector machine is time consuming method. Alternative approach to support vectormachine, is a simple, fast and analytically solvable linear modeling technique known as ‘Ridge regression’. It learns the dependency between the surface reflectance and illumination from a presented training sample of data. Ridge regression provides answer to the two fold motivation behind this work, i.e., stable and computationally simple approach. The proposed algorithms, ‘Support vector machine’ and ‘Ridge regression’ involves three step processes: First, an input matrix constructed from the preprocessed training data set is trained toobtain a trained model. Second, test images are presented to the trained model to obtain the chromaticity estimate of the illuminants present in the testing images. Finally, linear diagonal transformation is performed to obtain the color corrected image. The results show the effectiveness of the proposed algorithms on both calibrated and uncalibrated data set in comparison to the methods discussed in literature review. Finally, thesis concludes with a complete discussion and summary on comparison between the proposed approaches and other algorithms

The components of colour vision

Colour perception is formed of many different components, such as colour discrimination, colour constancy, colour term naming, and the dimensions of colour (hue, chroma and lightness). It is a ‘toolbox’ of processes, not one cohesive function. Some of the components of colour vision develop into adult-like function over childhood, but they do not necessarily mature at the same speed. The studies in this thesis investigate adult, child and infant colour perception and cognition. Paper 1 finds a relationship between colour constancy and colour term naming in three- to four-year-old children. This relationship has wider implications for the co-development of language and perception. Paper 2 (Rogers, Knoblauch & Franklin, 2016) uses the technique of Maximum Likelihood Conjoint Measurement (MLCM) in adult participants to investigate the interaction between lightness and chroma in perception. Paper 3 combines MLCM analysis with preferential looking methods to compare interaction of lightness and chroma in infant and adult participants. This study paves the way for the use of MLCM and eye-tracking for studying other dimensions in development such as face perception, language, surface and shape. Paper 4 investigates why discrimination is poorest along the blue-yellow direction of cone opponent space (also known as the daylight locus). We tested the theory that this is adaptive for colour constancy by comparing illumination discrimination to surface discrimination in adult participants. We found equally poor discrimination for blue-yellow in both conditions, suggesting colour constancy is not the only explanatory factor. Together, these papers add to our understanding of the key components of colour vision over the life span and how perception of colour depends on various contextual and individual factors. Furthermore, this thesis develops novel applications of experimental techniques, and paves the way for these methods to be used to study other cognitive and developmental domains