The Experts below are selected from a list of 321 Experts worldwide ranked by ideXlab platform
Wuzong Zhou - One of the best experts on this subject based on the ideXlab platform.
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formation crystal growth and Colour Appearance of mimetic tianmu glaze
Ceramics International, 2016Co-Authors: Changyang Chiang, Heather F Greer, R S Liu, Wuzong ZhouAbstract:Abstract Mimetic Tianmu glaze has been synthesised and analysed by using X-ray diffraction, energy-dispersive X-ray spectroscopy, scanning electron microscopy and transmission electron microscopy. It was found that the main body of the glaze was amorphous aluminium silicate with many embedded polycrystalline spherical particles of metal oxides containing manganese, cobalt, vanadium, bismuth and tungsten. Two dimensional spinel dendrite crystals of manganese, cobalt and aluminium oxide formed on the surface of the glaze. The formation mechanism of the microstructures in the Tianmu glaze is proposed. The Colour Appearance of the glaze has also been discussed. It has been found that the crystal thickness dependant light interference could be an important factor for the Appearance of rainbow-like Colour in the glaze layer.
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Formation, crystal growth and Colour Appearance of Mimetic Tianmu glaze
Ceramics International, 2016Co-Authors: Changyang Chiang, Heather F Greer, R S Liu, Wuzong ZhouAbstract:WZZ thanks EPSRC for financial support on FEG-SEM equipment (EP/F019580/1).Mimetic Tianmu glaze has been synthesized and analysed by using X-ray diffraction, energy-dispersive X-ray spectroscopy, scanning electron microscopy and transmission electron microscopy. It was found that the main body of the glaze was amorphous aluminium silicate with many embedded polycrystalline spherical particles of metal oxides containing manganese, cobalt, vanadium, bismuth and tungsten. Two dimensional spinel dendrites crystals of manganese, cobalt and aluminium oxide formed on the surface of the glaze. The formation mechanism of the microstructures in the Tianmu glaze is proposed. The Colour Appearance of the glaze has also been discussed. It has been found that the crystal thickness dependant light interference could be an important factor for the Appearance of rainbow-like Colour in the glaze layer.PostprintPeer reviewe
Ming Ronnier Luo - One of the best experts on this subject based on the ideXlab platform.
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zcam a Colour Appearance model based on a high dynamic range uniform Colour space
Optics Express, 2021Co-Authors: Muhammad Safdar, Jon Yngve Hardeberg, Ming Ronnier LuoAbstract:A Colour Appearance model based on a uniform Colour space is proposed. The proposed Colour Appearance model, ZCAM, comprises of comparatively simple mathematical equations, and plausibly agrees with the psychophysical phenomenon of Colour Appearance perception. ZCAM consists of ten Colour Appearance attributes including brightness, lightness, Colourfulness, chroma, hue angle, hue composition, saturation, vividness, blackness, and whiteness. Despite its relatively simpler mathematical structure, ZCAM performed at least similar to the CIE standard Colour Appearance model CIECAM02 and its revision, CAM16, in predicting a range of reliable experimental data.
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an extension of cam16 for predicting size effect and new Colour Appearance perceptions
Color Imaging Conference, 2018Co-Authors: Xiaoxuan Liu, Yoon Ji Cho, Kaida Xiao, Ming Ronnier LuoAbstract:CAM16 Colour Appearance model has been extended to predict the Appearance for stimulus of varying sizes and to provide new scales to evaluate saturation, vividness, whiteness and blackness.
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a comprehensive model of Colour Appearance for related and unrelated Colours of varying size viewed under mesopic to photopic conditions
Color Research and Application, 2017Co-Authors: Shou Ting Wei, Kaida Xiao, Ming Ronnier Luo, Michael R PointerAbstract:CIE has recommended two previous Appearance models, CIECAM97s and CIECAM02. However, these models are unable to predict the Appearance of a comprehensive range of Colours. The purpose of this study is to describe a new, comprehensive Colour Appearance model, which can be used to predict the Appearance of Colours under various viewing conditions that include a range of stimulus sizes, levels of illumination that range from scotopic through to photopic, and related and unrelated stimuli. In addition, the model has a uniform Colour space that provides a Colour-difference formula in terms of Colour Appearance parameters. © 2016 Wiley Periodicals, Inc. Col Res Appl, 42, 293–304, 2017
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the effectiveness of Colour Appearance attributes for enhancing image preference and naturalness
Color Imaging Conference, 2016Co-Authors: Yuteng Zhu, Ming Ronnier Luo, Peter Zsolt Bodrogi, Sebastian Fischer, Tran Quoc KhanhAbstract:Investigation of image quality on preference and naturalness using 1- dimensional and 2- dimensional Colour attributes was performed. Each Colour attribute varied in two directions, and each direction had two levels, i.e. large and small. In the present study, paired comparison was employed for image preference and categorical judgement for image naturalness assessment. The aim was to evaluate the performance and effectiveness of 1-dimensional and 2-dimensional Colour attributes on image quality. Furthermore, cultural difference, the relationship between image preference and naturalness, the difference between memory Colours in Colour patches and digital images were examined. The experimental results revealed that the effectiveness of Colour attributes on image quality vary with image content.
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CIECAM02 and Its Recent Developments
Advanced Color Image Processing and Analysis, 2012Co-Authors: Ming Ronnier LuoAbstract:The development of colorimetry can be divided into three stages: Colour specification, Colour difference evaluation and Colour Appearance modelling. Stage 1 considers the communication of Colour information by numbers. The second stage is Colour difference evaluation. While the CIE system has been successfully applied for over 80 years, it can only be used under quite limited viewing conditions, e.g., daylight illuminant, high luminance level, and some standardised viewing/illuminating geometries. However, with recent demands on crossmedia Colour reproduction, e.g., to match the Appearance of a Colour or an image on a display to that on hard copy paper, conventional colorimetry is becoming insufficient. It requires a Colour Appearance model capable of predicting Colour Appearance across a wide range of viewing conditions so that Colour Appearance modelling becomes the third stage of colorimetry. Some call this as advanced colorimetry. This chapter will focused on the recent developments based on CIECAM02.
Alastair R. Allen - One of the best experts on this subject based on the ideXlab platform.
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ACIVS - An Image Quality Metric Based on a Colour Appearance Model
Advanced Concepts for Intelligent Vision Systems, 2008Co-Authors: Alastair R. AllenAbstract:Image quality metrics have been widely used in imaging systems to maintain and improve the quality of images being processed and transmitted. Due to the close relationship between image quality and human visual perception, both computer scientists and psychologists have contributed to the development of image quality metrics. In this paper, a novel image quality metric using a Colour Appearance model is proposed. After the physical Colour stimuli of the images being compared are transformed into perceptual Colour Appearance attributes, the distortion measures between the corresponding attributes are used to predict the subjective scores of image quality, by use of data-driven models: Multiple Linear Regression (MLR), General Regression Neural Network (GRNN) and Back-Propagation Neural Network (BPNN). Based on the data-driven model used, we have developed three image quality metrics, CAM_MLR, CAM_GRNN and CAM_BPNN. The experiments have shown that the performance of CAM_BPNN is better than the well-known image quality metric SSIM.
Alastair Allen - One of the best experts on this subject based on the ideXlab platform.
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an image quality metric based on a Colour Appearance model
Advanced Concepts for Intelligent Vision Systems, 2008Co-Authors: Li Cui, Alastair AllenAbstract:Image quality metrics have been widely used in imaging systems to maintain and improve the quality of images being processed and transmitted. Due to the close relationship between image quality and human visual perception, both computer scientists and psychologists have contributed to the development of image quality metrics. In this paper, a novel image quality metric using a Colour Appearance model is proposed. After the physical Colour stimuli of the images being compared are transformed into perceptual Colour Appearance attributes, the distortion measures between the corresponding attributes are used to predict the subjective scores of image quality, by use of data-driven models: Multiple Linear Regression (MLR), General Regression Neural Network (GRNN) and Back-Propagation Neural Network (BPNN). Based on the data-driven model used, we have developed three image quality metrics, CAM_MLR, CAM_GRNN and CAM_BPNN. The experiments have shown that the performance of CAM_BPNN is better than the well-known image quality metric SSIM.
Sean Moran - One of the best experts on this subject based on the ideXlab platform.
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robust fusion of Colour Appearance models for object tracking
British Machine Vision Conference, 2004Co-Authors: Christopher Town, Sean MoranAbstract:This paper reports on work which fuses three different Appearance models to enable robust tracking of multiple objects on the basis of Colour. Short-term variation in object Colour is modelled non-parametrically using adaptive binning histograms. Appearance changes at intermediate time scales are represented by semi-parametric (Gaussian mixture) models while a parametric subspace method (Robust PCA) is employed to model long term stable Appearance. Fusion of the three models is achieved through particle filtering and the Democratic integration method. It is shown how robust estimation and adaptation of the models both individually and in combination results in improved visual tracking accuracy.
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BMVC - Robust Fusion of Colour Appearance Models for Object Tracking
Procedings of the British Machine Vision Conference 2004, 2004Co-Authors: Christopher Town, Sean MoranAbstract:This paper reports on work which fuses three different Appearance models to enable robust tracking of multiple objects on the basis of Colour. Short-term variation in object Colour is modelled non-parametrically using adaptive binning histograms. Appearance changes at intermediate time scales are represented by semi-parametric (Gaussian mixture) models while a parametric subspace method (Robust PCA) is employed to model long term stable Appearance. Fusion of the three models is achieved through particle filtering and the Democratic integration method. It is shown how robust estimation and adaptation of the models both individually and in combination results in improved visual tracking accuracy.