Robust Chroma and Lightness Descriptors

New descriptors for lightness and chroma are presented that are based on properties of a wraparound Gaussian metameric to the given XYZ tristimulus coordinates. For the 1600 samples of the Munsell glossy set, both descriptors are found to correlate to Munsell value and chroma at least as well as the corresponding CIECAM02 descriptors when the Munsell samples are under the CIE C illuminant. However, when the illuminant is changed the new descriptors were found to be considerably more consistent under the second illuminant than those of CIECAM02

Gaussian Illuminants and Reflectances for Colour Signal Prediction

An alternative to the von Kries scaling underlying the chromatic adaptation transforms found in colour appearance models such as CIECAM02 is suggested for predicting what the colour signal (e.g., XYZ) reflected from a surface under a first illuminant is likely to become when lit instead by a second illuminant. The proposed method, G2M, employs metameric Gaussian-like functions to model the illuminant and reflectance spectra. The method’s prediction is based on relighting the Gaussian-like reflectance spectrum with the second Gaussian-like illuminant. Tests show that the proposed G2M method significantly outperforms CIECAT02

Hue Correlate Stability using a Gaussian versus Rectangular Object-Colour Atlas

The perceptual correlate to hue and the stability of its representation in the coordinates of Logvinenko\u27s illumination-invariant object-colour atlas (Logvinenko, 2009) are investigated. Logvinenko\u27s object-colour atlas represents the colours of objects in terms of special rectangular reflectance functions defined by 3-parameters, a (chromatic purity), o (spectral bandwidth) and A. (central wavelength) describing the rectangular reflectance to which it is metameric. These parameters were shown to be approximate perceptual correlates in terms of chroma, whiteness/blackness, and hue, respectively. When the illumination changes, the mapping of object colours to the rectangular atlas coordinates is subject to a phenomenon referred to as colour stimulus shift. The perceptual correlates shift as well. The problem of coJour stinmlus shift is exacerbated by the fact that the atlas is based on rectangular functions. This paper explores the benefits of using the Gaussian parameterization of the object-colour atlas (Logvinenko, 20 12) in terms of its robustness to colour stimulus shift and in terms of how well it maps to the perceptual correlate ofhue

A Robust Hue Descriptor

A hue descriptor based on Logvinenko’s illuminantinvariant object colour atlas [1] is tested in terms of how well it maps hues to the hue names found in Moroney’s Colour Thesaurus [2] [3] and how well it maps hues of Munsell papers to their corresponding Munsell hue designator. Called the KSM hue descriptor, it correlates hue with the central wavelength of a Gaussian-shaped reflectance function. An important feature of this representation is that the set of hue descriptors inherits the illuminate invariant property of Logvinenko’s object colour atlas. Despite the illuminant invariance of the atlas and the hue descriptors, metamer mismatching means that colour stimulus shift [4] can occur, which will inevitably lead to some hue shifts. However, tests show that KSM hue is robust in the sense that it is much more stable under a change of illuminant than CIELAB hue

Gaussian-Based Hue Descriptors

A robust and accurate hue descriptor that is useful in modeling human color perception and for computer vision applications is explored. The hue descriptor is based on the peak wavelength of a Gaussian-like function (called a wraparound Gaussian) and is shown to correlate as well as CIECAM02 hue to the hue designators of papers from the Munsell and Natural Color System color atlases and to the hue names found in Moroney’s Color Thesaurus. The new hue descriptor is also shown to be significantly more stable under a variety of illuminants than CIECAM02. The use of wraparound Gaussians as a hue model is similar in spirit to the use of subtractive Gaussians proposed by Mizokami et al., but overcomes many of their limitations

Metamer Mismatching as a Measure of the Color Rendering of Lights

We propose a new method for evaluating the colour rendering properties of lights. The new method uses the degree of metamer mismatching for the CIE XYZ corresponding to flat grey (constant reflectance of 0.5) quantified in terms of the metamer mismatch volume index proposed by Logvinenko et al. (Logvinenko 2014). A major advantage of this method is that unlike many previous color rendering indices it does not depend on the properties of a chosen set of representative test objects

Intersecting Color Manifolds

Logvinenko’s color atlas theory provides a structure in which a complete set of color-equivalent material and illumination pairs can be generated to match any given input RGB color. In chromaticity space, the set of such pairs forms a 2-dimensional manifold embedded in a 4-dimensional space. For singleilluminant scenes, the illumination for different input RGB values must be contained in all the corresponding manifolds. The proposed illumination-estimation method estimates the scene illumination based on calculating the intersection of the illuminant components of the respective manifolds through a Hough-like voting process. Overall, the performance on the two datasets for which camera sensitivity functions are available is comparable to existing methods. The advantage of the formulating the illumination-estimation in terms of manifold intersection is that it expresses the constraints provided by each available RGB measurement within a sound theoretical foundation

Electromagnetic Analysis and Design of Semiconductor Qubit Structures for the Realization of the Quantum Computer

Ph.DDOCTOR OF PHILOSOPH

Object-Color Description Under Varying Illumination

Given a fixed and uniform illumination, metameric objects appear as the same color. However, when the illumination is altered, two metameric reflecting objects under the first illuminant may no longer produce the same color signal under the second. This situation is called metamer mismatching. Metamer mismatching poses several challenges for the camera and display industries as well as color-based computer vision technology.In light of metamer mismatching, the present study criticizes the conventional approaches to color description when the illuminant alters, and then lays a foundation to robustly describe object colors under varying illumination conditions. Later, the degree of metamer mismatching is used as a measure of the quality of lights. We demonstrate that although the common color spaces such as CIELAB and related spaces in the literature may work well for a fixed illuminant, they can lead to poor results when the illuminant is changed. In view of these problems, new descriptors for hue, lightness and chroma are presented that are based on properties of a Gaussian-like spectrum metameric to the given color tristimulus coordinates. Experiments show that the new Gaussian-based appearance descriptors correlate with different descriptors as well as the CIECAM02 appearance model does on average. Furthermore, the Gaussian-based descriptors are significantly more stable than the descriptors defined in the CIECAM02 appearance model.Afterwards, the problem of predicting how the color signal arising in response to light reflected from the surface of an object is likely to change when the lighting alters is investigated. A new method, called the Gaussian Metamer (GM) method is proposed for predicting what a color signal observed from a surface under a first light is likely to be when the same surface is lit instead by a second light. Due to metamer mismatching, there is not a unique answer for this problem. Our approach is to use one of the possible metamers that is likely to do well on average. The results outperform other state-of-the-art prediction methods

Camera Color Accuracy Evaluated via Metamer Mismatch Moments

A novel method for evaluating the colorimetric accuracy of digital color cameras is proposed based on a new measure of metamer mismatch body (MMB) induced by the change from the camera as an observer to the human standard observer. Previous methods of evaluating the colorimetric accuracy of a camera at the Luther condition [1], the mean CIE&nbsp