A real-time neural system for color constancy

A neural network approach to the problem of color constancy is presented. Various algorithms based on Land's retinex theory are discussed with respect to neurobiological parallels, computational efficiency, and suitability for VLSI implementation. The efficiency of one algorithm is improved by the application of resistive grids and is tested in computer simulations; the simulations make clear the strengths and weaknesses of the algorithm. A novel extension to the algorithm is developed to address its weaknesses. An electronic system that is based on the original algorithm and that operates at video rates was built using subthreshold analog CMOS VLSI resistive grids. The system displays color constancy abilities and qualitatively mimics aspects of human color perception

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

Wavelet-Based Enhancement Technique for Visibility Improvement of Digital Images

Image enhancement techniques for visibility improvement of color digital images based on wavelet transform domain are investigated in this dissertation research. In this research, a novel, fast and robust wavelet-based dynamic range compression and local contrast enhancement (WDRC) algorithm to improve the visibility of digital images captured under non-uniform lighting conditions has been developed. A wavelet transform is mainly used for dimensionality reduction such that a dynamic range compression with local contrast enhancement algorithm is applied only to the approximation coefficients which are obtained by low-pass filtering and down-sampling the original intensity image. The normalized approximation coefficients are transformed using a hyperbolic sine curve and the contrast enhancement is realized by tuning the magnitude of the each coefficient with respect to surrounding coefficients. The transformed coefficients are then de-normalized to their original range. The detail coefficients are also modified to prevent edge deformation. The inverse wavelet transform is carried out resulting in a lower dynamic range and contrast enhanced intensity image. A color restoration process based on the relationship between spectral bands and the luminance of the original image is applied to convert the enhanced intensity image back to a color image. Although the colors of the enhanced images produced by the proposed algorithm are consistent with the colors of the original image, the proposed algorithm fails to produce color constant results for some pathological scenes that have very strong spectral characteristics in a single band. The linear color restoration process is the main reason for this drawback. Hence, a different approach is required for tackling the color constancy problem. The illuminant is modeled having an effect on the image histogram as a linear shift and adjust the image histogram to discount the illuminant. The WDRC algorithm is then applied with a slight modification, i.e. instead of using a linear color restoration, a non-linear color restoration process employing the spectral context relationships of the original image is applied. The proposed technique solves the color constancy issue and the overall enhancement algorithm provides attractive results improving visibility even for scenes with near-zero visibility conditions. In this research, a new wavelet-based image interpolation technique that can be used for improving the visibility of tiny features in an image is presented. In wavelet domain interpolation techniques, the input image is usually treated as the low-pass filtered subbands of an unknown wavelet-transformed high-resolution (HR) image, and then the unknown high-resolution image is produced by estimating the wavelet coefficients of the high-pass filtered subbands. The same approach is used to obtain an initial estimate of the high-resolution image by zero filling the high-pass filtered subbands. Detail coefficients are estimated via feeding this initial estimate to an undecimated wavelet transform (UWT). Taking an inverse transform after replacing the approximation coefficients of the UWT with initially estimated HR image, results in the final interpolated image. Experimental results of the proposed algorithms proved their superiority over the state-of-the-art enhancement and interpolation techniques

Digital Color Imaging

This paper surveys current technology and research in the area of digital color imaging. In order to establish the background and lay down terminology, fundamental concepts of color perception and measurement are first presented us-ing vector-space notation and terminology. Present-day color recording and reproduction systems are reviewed along with the common mathematical models used for representing these devices. Algorithms for processing color images for display and communication are surveyed, and a forecast of research trends is attempted. An extensive bibliography is provided

Semantik renk değişmezliği

Color constancy aims to perceive the actual color of an object, disregarding the effectof the light source. Recent works showed that utilizing the semantic information inan image enhances the performance of the computational color constancy methods.Considering the recent success of the segmentation methods and the increased numberof labeled images, we propose a color constancy method that combines individualilluminant estimations of detected objects which are computed using the classes of theobjects and their associated colors. Then we introduce a weighting system that valuesthe applicability of the object classes to the color constancy problem. Lastly, weintroduce another metric expressing the detected object and how well it fits the learnedmodel of its class. Finally, we evaluate our proposed method on a popular colorconstancy dataset, confirming that each weight addition enhances the performanceof the global illuminant estimation. Experimental results show promising results,outperforming the conventional methods while competing with the state of the artmethods.--M.S. - Master of Scienc

Particle Filters for Colour-Based Face Tracking Under Varying Illumination

Automatic human face tracking is the basis of robotic and active vision systems used for facial feature analysis, automatic surveillance, video conferencing, intelligent transportation, human-computer interaction and many other applications. Superior human face tracking will allow future safety surveillance systems which monitor drowsy drivers, or patients and elderly people at the risk of seizure or sudden falls and will perform with lower risk of failure in unexpected situations. This area has actively been researched in the current literature in an attempt to make automatic face trackers more stable in challenging real-world environments. To detect faces in video sequences, features like colour, texture, intensity, shape or motion is used. Among these feature colour has been the most popular, because of its insensitivity to orientation and size changes and fast process-ability. The challenge of colour-based face trackers, however, has been dealing with the instability of trackers in case of colour changes due to the drastic variation in environmental illumination. Probabilistic tracking and the employment of particle filters as powerful Bayesian stochastic estimators, on the other hand, is increasing in the visual tracking field thanks to their ability to handle multi-modal distributions in cluttered scenes. Traditional particle filters utilize transition prior as importance sampling function, but this can result in poor posterior sampling. The objective of this research is to investigate and propose stable face tracker capable of dealing with challenges like rapid and random motion of head, scale changes when people are moving closer or further from the camera, motion of multiple people with close skin tones in the vicinity of the model person, presence of clutter and occlusion of face. The main focus has been on investigating an efficient method to address the sensitivity of the colour-based trackers in case of gradual or drastic illumination variations. The particle filter is used to overcome the instability of face trackers due to nonlinear and random head motions. To increase the traditional particle filter\u27s sampling efficiency an improved version of the particle filter is introduced that considers the latest measurements. This improved particle filter employs a new colour-based bottom-up approach that leads particles to generate an effective proposal distribution. The colour-based bottom-up approach is a classification technique for fast skin colour segmentation. This method is independent to distribution shape and does not require excessive memory storage or exhaustive prior training. Finally, to address the adaptability of the colour-based face tracker to illumination changes, an original likelihood model is proposed based of spatial rank information that considers both the illumination invariant colour ordering of a face\u27s pixels in an image or video frame and the spatial interaction between them. The original contribution of this work lies in the unique mixture of existing and proposed components to improve colour-base recognition and tracking of faces in complex scenes, especially where drastic illumination changes occur. Experimental results of the final version of the proposed face tracker, which combines the methods developed, are provided in the last chapter of this manuscript

Colour Constancy: Cues, Priors and Development

Colour is crucial for detecting, recognising, and interacting with objects. However, the reflected wavelength of light ("colour") varies vastly depending on the illumination. Whilst adults can judge colours as relatively invariant under changing illuminations (colour constancy), much remains unknown, which this thesis aims to resolve. Firstly, previous studies have shown adults can use certain cues to estimate surface colour. However, one proposed cue - specular highlights - has been little researched so this is explored here. Secondly, the existing data on a daylight prior for colour constancy remain inconclusive so we aimed to further investigate this. Finally, no studies have investigated the development of colour constancy during childhood so the third aim is to determine at what age colour constancy becomes adult-like. In the introduction, existing research is discussed, including cues to the illuminant, daylight priors, and the development of perceptual constancies. The second chapter contains three experiments conducted to determine whether adults can use a specular highlight cue and/ or daylight prior to aid colour constancy. Results showed adults can use specular highlights when other cues are weakened. Evidence for a daylight prior was weak. In the third chapter the development of colour constancy during childhood was investigated by developing a novel child-friendly task. Children had higher constancy than adults, and evidence for a daylight prior was mixed. The final experimental chapter used the task developed in Chapter 3 to ask whether children can use specular highlights as a cue for colour constancy. Testing was halted early due to the coronavirus pandemic, yet the data obtained suggest that children are negatively impacted by specular highlights. Finally, in the general discussion, the results of the six experiments are brought together to draw conclusions regarding the use of cues and priors, and the development of colour constancy. Implications and future directions for research are discussed

The time-course of colour vision

Four experiments are presented, each investigating temporal properties of colour vision processing in human observers. The first experiment replicates and extends an experiment by Stromeyer et al. (1991). We look for a phase difference between combined temporal modulations in orthogonal directions in colour space, which might null the often-claimed latency of signals originating from the short-wavelength sensitive cones (S-cones). We provide another estimate of the magnitude of this latency, and give evidence to suggest that it originates early in the chromatic pathway, before signals from S-cones are combined with those that receive opposed L- and M-cone input. In the second experiment we adapt observers to two stimuli that are matched in the mean and amplitude of modulation they offer to the cone classes and to the cardinal opponent mechanisms, but that differ in chromatic appearance, and hence their modulation of later colour mechanisms. Chromatic discrimination thresholds after adaptation to these two stimuli differ along intermediate directions in colour space, and we argue that these differences reveal the adaptation response of central colour mechanisms. In the third experiment we demonstrate similar adaptation using the same stimuli, measured with reaction times rather than thresholds. In the final experiment, we measure the degree to which colour constancy is achieved as a function of time in a simulated stimulus environment in which the illuminant changes periodically. We find that perfect constancy is not achieved instantaneously after an illuminant chromaticity shift and that constancy of colour appearance judgements increases over several seconds