Color constancy based on the Grey-edge hypothesis

International audienceA well-known color constancy method is based on the Grey-World assumption i.e. the average reflectance of surfaces in the world is achromatic. In this article we propose a new hypothesis for color constancy, namely the Grey-Edge hypothesis assuming that the average edge difference in a scene is achromatic. Based on this hypothesis, we propose an algorithm for color constancy. Recently, the Grey-World hypothesis and the max-RGB method were shown to be two instantiations of a Minkowski norm based color constancy method. Similarly we also propose a more general version of the Grey-Edge hypothesis which assumes that the Minkowsky norm of derivatives of the reflectance of surfaces is achromatic. The algorithms are tested on a large data set of images under different illuminants, and the results show that the new method outperforms the Grey-World assumption and the max-RGB method. Results are comparable to more elaborate algorithms, however at lower computational costs

Coloring local feature extraction

International audienceAlthough color is commonly experienced as an indispensable quality in describing the world around us, state-of-the art local feature-based representations are mostly based on shape description, and ignore color information. The description of color is hampered by the large amount of variations which causes the measured color values to vary significantly. In this paper we aim to extend the description of local features with color information. To accomplish a wide applicability of the color descriptor, it should be robust to : 1. photometric changes commonly encountered in the real world, 2. varying image quality, from high quality images to snap-shot photo quality and compressed internet images. Based on these requirements we derive a set of color descriptors. The set of proposed descriptors are compared by extensive testing on multiple applications areas, namely, matching, retrieval and classification, and on a wide variety of image qualities. The results show that color descriptors remain reliable under photometric and geometrical changes, and with decreasing image quality. For all experiments a combination of color and shape outperforms a pure shape-based approach

Highlights Analysis System (HAnS) for low dynamic range to high dynamic range conversion of cinematic low dynamic range content

We propose a novel and efficient algorithm for detection of specular reflections and light sources (highlights) in cinematic content. The detection of highlights is important for reconstructing them properly in the conversion of the low dynamic range (LDR) to high dynamic range (HDR) content. Highlights are often difficult to be distinguished from bright diffuse surfaces, due to their brightness being reduced in the conventional LDR content production. Moreover, the cinematic LDR content is subject to the artistic use of effects that change the apparent brightness of certain image regions (e.g. limiting depth of field, grading, complex multi-lighting setup, etc.). To ensure the robustness of highlights detection to these effects, the proposed algorithm goes beyond considering only absolute brightness and considers five different features. These features are: the size of the highlight relative to the size of the surrounding image structures, the relative contrast in the surrounding of the highlight, its absolute brightness expressed through the luminance (luma feature), through the saturation in the color space (maxRGB feature) and through the saturation in white (minRGB feature). We evaluate the algorithm on two different image data-sets. The first one is a publicly available LDR image data-set without cinematic content, which allows comparison to the broader State of the art. Additionally, for the evaluation on cinematic content, we create an image data-set consisted of manually annotated cinematic frames and real-world images. For the purpose of demonstrating the proposed highlights detection algorithm in a complete LDR-to-HDR conversion pipeline, we additionally propose a simple inverse-tone-mapping algorithm. The experimental analysis shows that the proposed approach outperforms conventional highlights detection algorithms on both image data-sets, achieves high quality reconstruction of the HDR content and is suited for use in LDR-to-HDR conversion

Investigations into colour constancy by bridging human and computer colour vision

PhD ThesisThe mechanism of colour constancy within the human visual system has long been of great interest to researchers within the psychophysical and image processing communities. With the maturation of colour imaging techniques for both scientific and artistic applications the importance of colour capture accuracy has consistently increased. Colour offers a great deal more information for the viewer than grayscale imagery, ranging from object detection to food ripeness and health estimation amongst many others. However these tasks rely upon the colour constancy process in order to discount scene illumination to allow these tasks to be carried out. Psychophysical studies have attempted to uncover the inner workings of this mechanism, which would allow it to be reproduced algorithmically. This would allow the development of devices which can eventually capture and perceive colour in the same manner as a human viewer. These two communities have approached this challenge from opposite ends, and as such very different and largely unconnected approaches. This thesis investigates the development of studies and algorithms which bridge the two communities. Utilising findings from psychophysical studies as inspiration to firstly improve an existing image enhancement algorithm. Results are then compared to state of the art methods. Then, using further knowledge, and inspiration, of the human visual system to develop a novel colour constancy approach. This approach attempts to mimic and replicate the mechanism of colour constancy by investigating the use of a physiological colour space and specific scene contents to estimate illumination. Performance of the colour constancy mechanism within the visual system is then also investigated. The performance of the mechanism across different scenes and commonly and uncommonly encountered illuminations is tested. The importance of being able to bridge these two communities, with a successful colour constancy method, is then further illustrated with a case study investigating the human visual perception of the agricultural produce of tomatoes.EPSRC DTA: Institute of Neuroscience, Newcastle University

Conception et mise en oeuvre d'un système de visualisation contextuelle

Entre l'acquisition de l'image et son affichage, il y a plusieurs opérations que l'image subit.En plus, les écrans ne sont pas capables d'afficher les images avec une grande fidélité. Ce travail consiste à corriger l'image avant son affichage. Les corrections apportées dépendent essentiellement des spécificités de l'usager comme les caractéristiques de la rétine et les différents aspects de la perception des couleurs. Elles dépendent aussi de l'environnement qui intervient par l'intensité et la couleur de la lumière. Enfin, elles dépendent des caractéristiques de l'écran qui influencent l'affichage avec son gamut, son intensité maximale et sa consommation en énergie. Notre objectif est de créer un système qui prend en charge tous ces paramètres et qui nous fournit à la sortie une image qui satisfasse l'utilisateur

High-fidelity colour reproduction for high-dynamic-range imaging

The aim of this thesis is to develop a colour reproduction system for high-dynamic-range (HDR) imaging. Classical colour reproduction systems fail to reproduce HDR images because current characterisation methods and colour appearance models fail to cover the dynamic range of luminance present in HDR images. HDR tone-mapping algorithms have been developed to reproduce HDR images on low-dynamic-range media such as LCD displays. However, most of these models have only considered luminance compression from a photographic point of view and have not explicitly taken into account colour appearance. Motivated by the idea to bridge the gap between crossmedia colour reproduction and HDR imaging, this thesis investigates the fundamentals and the infrastructure of cross-media colour reproduction. It restructures cross-media colour reproduction with respect to HDR imaging, and develops a novel cross-media colour reproduction system for HDR imaging. First, our HDR characterisation method enables us to measure HDR radiance values to a high accuracy that rivals spectroradiometers. Second, our colour appearance model enables us to predict human colour perception under high luminance levels. We first built a high-luminance display in order to establish a controllable high-luminance viewing environment. We conducted a psychophysical experiment on this display device to measure perceptual colour attributes. A novel numerical model for colour appearance was derived from our experimental data, which covers the full working range of the human visual system. Our appearance model predicts colour and luminance attributes under high luminance levels. In particular, our model predicts perceived lightness and colourfulness to a significantly higher accuracy than other appearance models. Finally, a complete colour reproduction pipeline is proposed using our novel HDR characterisation and colour appearance models. Results indicate that our reproduction system outperforms other reproduction methods with statistical significance. Our colour reproduction system provides high-fidelity colour reproduction for HDR imaging, and successfully bridges the gap between cross-media colour reproduction and HDR imaging

Uses of uncalibrated images to enrich 3D models information

The decrease in costs of semi-professional digital cameras has led to the possibility for everyone to acquire a very detailed description of a scene in a very short time. Unfortunately, the interpretation of the images is usually quite hard, due to the amount of data and the lack of robust and generic image analysis methods. Nevertheless, if a geometric description of the depicted scene is available, it gets much easier to extract information from 2D data. This information can be used to enrich the quality of the 3D data in several ways. In this thesis, several uses of sets of unregistered images for the enrichment of 3D models are shown. In particular, two possible fields of application are presented: the color acquisition, projection and visualization and the geometry modification. Regarding color management, several practical and cheap solutions to overcome the main issues in this field are presented. Moreover, some real applications, mainly related to Cultural Heritage, show that provided methods are robust and effective. In the context of geometry modification, two approaches are presented to modify already existing 3D models. In the first one, information extracted from images is used to deform a dummy model to obtain accurate 3D head models, used for simulation in the context of three-dimensional audio rendering. The second approach presents a method to fill holes in 3D models, with the use of registered images depicting a pattern projected on the real object. Finally, some useful indications about the possible future work in all the presented fields are given, in order to delineate the developments of this promising direction of research