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检索条件"任意字段=Colour and Visual Computing Symposium"

共 114 条记录，以下是31-40 订阅

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Deep Learning for Dehazing: Comparison and Analysis

Deep Learning for Dehazing: Comparison and Analysis

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2018 colour and visual computing symposium, CVCS 2018

作者： Valeriano, Leonel Cuevas Thomas, Jean-Baptiste Benoit, Alexandre Norwegian Colour and Visual Computing Laboratory NTNU Gjovik Norway LISTIC Univ. Savoie Mont Blanc Annecy France

ISBN: (纸本)9781538656457

We compare a recent dehazing method based on deep learning, Dehazenet, with traditional state-of-the-art approaches, on benchmark data with reference. Dehazenet estimates the depth map from transmission factor on a single color image, which is used to inverse the Koschmieder model of imaging in the presence of haze. In this sense, the solution is still attached to the Koschmieder model. We demonstrate that the transmission is very well estimated by the network, but also that this method exhibits the same limitation than others due to the use of the same imaging model. © 2018 IEEE.

关键词： Deep learning

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Comparison of Mosaic Patterns for Spectral Filter Arrays

Comparison of Mosaic Patterns for Spectral Filter Arrays

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2018 colour and visual computing symposium, CVCS 2018

作者： Gigilashvili, Davit Hardeberg, Jon Yngve Thomas, Jean-Baptiste Department of Computer Science Norwegian Colour and Visual Computing Laboratory NTNU - The Norwegian University of Science and Technology Gjovik Norway

ISBN: (纸本)9781538656457

Spectral Filter Arrays allow snapshot multispectral acquisition within a compact camera. While Bayer filter mosaic is a widely accepted standard for color filter arrays, no single mosaic pattern is considered dominant for spectral filter arrays. We compare different patterns for 8-band mosaics, and their overall performance in terms of spectral reconstruction, as well as color and structure reproduction. We demonstrate that some mosaics having overrepresentation of certain filters perform better than the ones with overrepresentaiton of other filters, while the arrays having all filters equally represented perform better than the arrays with overrepresentation. © 2018 IEEE.

关键词： Cell proliferation

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Enhancing dermoscopy images to improve melanoma detection

Enhancing dermoscopy images to improve melanoma detection

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2018 colour and visual computing symposium, CVCS 2018

作者： Cherepkova, Olga Hardeberg, Jon Yngve Norwegian Colour and Visual Computing Laboratory Department of Computer Science NTNU - The Norwegian University of Science and Technology Gjovik Norway

ISBN: (纸本)9781538656457

Since the application of image analysis algorithms has received much interest in the field of medical imaging, particularly to aid physician with their diagnosis, ways of improving the analysis accuracy in this field has become an important research question. In this work we investigate into the performance analysis of an automatic lesion classification algorithm proposed for skin cancer detection. We show that enhancement and color correction of the original lesion images have a positive impact on the further cancer detection, in the process of automatic classification and visual judgment. The purpose of the work is to analyze the influence of different image enhancement and color correction methods on efficiency of melanoma detection results, tested on a given set of dermoscopy images and a previously developed CNN-based detection algorithm. © 2018 IEEE.

关键词： Image enhancement

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Methods for psychophysical assessment of colour difference by observers with a colour vision deficiency

Methods for psychophysical assessment of colour difference b...

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2018 colour and visual computing symposium, CVCS 2018

作者： Kvitle, Anne Kristin Oddløkken, Henrik Green, Phil Nussbaum, Peter Norwegian Colour and Visual Computing Laboratory Norwegian University of Science and Technology Gjovik Norway

ISBN: (纸本)9781538656457

This study compares two designs of psychophysical used for colour difference experiments for two classes of observers, those with normal colour vision and those with a colour vision deficiency. A grey scale pair experiment was conducted on a computer display including two groups of observers;15 deutan type colour vision deficient observers and a reference group of 15 observers with normal colour vision. Here, the participants assessed 194 colour pairs from 8 colour centers. Each colour center had variations in lightness, chroma and hue relative to a reference colour. Each colour pair consisted of a reference colour and a variation, and the subjects compared the colour difference in this pair against the differences in a set of 6 neutral grey scale pairs. Additionally, based on the same colour centers and variations, a Two-Alternative Forced Choice (2AFC) experiment was conducted where observers selected the largest difference between a reference colour and the two alternative sample colours, and subsequently scaled the perceived difference from a category scale. The STandardized Residual Sum of Squares (STRESS) was used to evaluate the coherence between the visual and the computed colour difference. Intra-observer and inter-observer variations are used to describe the variation and repeatability. A comparison of the visual and computed colour difference for the observer groups shows a lower visual score and a higher dispersion for the CVD observer group. There are also higher inter-observer variability, which is expected as the severeness of the conditions varies from nearly normal to strongly affected. However, the STRESS results are at the level of normal performance for some of the selected colour centers. The 2AFC method give better STRESS results for both observer groups. © 2018 IEEE.

关键词： Color vision

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colour-to-Greyscale Image Conversion by Linear Anisotropic Diffusion of Perceptual colour Metrics

Colour-to-Greyscale Image Conversion by Linear Anisotropic D...

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2018 colour and visual computing symposium, CVCS 2018

作者： Farup, Ivar Pedersen, Marius Alsam, Ali Department of Computer Science Norwegian University of Science and Technology Gjøvik Norway Department of Computer Science Norwegian University of Science and Technology Trondheim Norway

ISBN: (纸本)9781538656457

We present an algorithm for conversion of colour images to greyscale. The underlying idea is that local perceptual colour differences in the colour image should translate into local differences in greylevel in the greyscale image. This is obtained by constructing a gradient for the greyscale image from the eigenvalues and eigenvectors of the structure tensor of the colour image, which, in turn, is computed by means of perceptual colour difference metrics. The greyscale image is then constructed from the gradient by means of linear anisotropic diffusion, where the diffusion tensor is constructed from the same structure tensor. By means of psychometric experiments, it is found that the algorithm gives the most accurate image reproduction when used with the ΔE99 colour metric, and that it performs at the level of, or better than, other state-of-the-art spatial algorithms. Surprisingly, the only algorithm that can compete in terms of accuracy is a simple luminance map computed as the L∗ channel of the image represented in the CIELAB colour space. © 2018 IEEE.

关键词： Color

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Novel Approach to Uniformization of a Color Space via Generic Deep Learning-Based Transformation

Novel Approach to Uniformization of a Color Space via Generi...

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2018 colour and visual computing symposium, CVCS 2018

作者： Sidorov, Oleksii Norwegian Colour and Visual Computing Laboratory NTNU Gjovik Norway

ISBN: (纸本)9781538656457

Creation of a convenient uniform color space which will match experimental data and will be easy-to-use - one of a primary objectives of color science. In this work we present novel approach which transform any existing color space in order to make the discrimination ellipses unit circles. This allows to find color difference in a new color space as Euclidian distance with constant unit threshold. A priori, color difference in a new color space should match perceptual color difference, since transformation is based on experimental data. The lack of experimental data for every point may be overcame via deep learning-based regression model, namely, multilayer perceptron which takes color coordinates as input and returns ellipses' parameters as output. Results are demonstrated on MacAdam's ellipses in xy Chromaticity Diagram and Luo and Rigg chromaticity-discrimination ellipses in a∗b∗ chromaticity plane. Additionally, topic of fitting discrimination ellipses is covered. © 2018 IEEE.

关键词： Color

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Evaluation of Gamut Mapping Algorithms in different Uniform colour Spaces

Evaluation of Gamut Mapping Algorithms in different Uniform ...

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2018 colour and visual computing symposium, CVCS 2018

作者： Zhao, Baiyue Xu, Lihao Luo, Ming Ronnier Safdar, Muhammad State Key Laboratory of Modern Optical Instrument Zhejiang University Hangzhou China Department of Computer Science COMSATS Institute of Information Technology Sahiwal Pakistan

ISBN: (纸本)9781538656457

Gamut mapping is an important component in colour management and has drawn much attention in the last decades. However, previous researches mainly focused gamut mapping algorithms (GMAs) and paid little attention to the uniform colour space (UCS) where gamut mapping was taken place. In this paper, two new GMAs were proposed and compared with other commonly adopted GMAs. Two specific UCSs, i.e. CAM16-UCS and Jzazbz were tested by a psychophysical experiment to verify their impact on the mapping performance. Experimental results show that a newly proposed GMA based on vividness perception performed well and Jzazbz is a promising UCS for gamut mapping. © 2018 IEEE.

关键词： Color

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Validation of stereo vision based liver surface reconstruction for image guided surgery

Validation of stereo vision based liver surface reconstructi...

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2018 colour and visual computing symposium, CVCS 2018

作者： Andrea, Teatini Congcong, Wang Rafael, Palomar Faouzi, Alaya Cheikh Azeddine, Beghdadi Bjørn, Edwin Jakob, Elle Ole Intervention Centre Oslo University Hospital Oslo Norway Norwegian Colour and Visual Computing Lab Norwegian University of Science and Technology Gjovik Norway Department of Informatics University of Oslo Oslo Norway L2TI-Institut Galilée Université Paris 13 Sorbonne Paris Cité Villetaneuse France Oslo University Hospital Department of Hepato-Pancreatic-Biliary Surgery Oslo Norway

ISBN: (纸本)9781538656457

Image guided surgery systems aim to provide navigation to surgeons in order to improve accuracy and safety of the procedures. Through stereo reconstruction algorithms, it is possible to generate 3D surfaces intra-operatively by means of a laparoscopic stereo-camera. This study aims to setup a simulation system and quantitatively validate a recent proposed reconstruction algorithm with application to laparoscopic liver resection surgery. The intra-operative surface will be used to guide model to patient registration. This will also improve accuracy of the navigation by correcting intra-operative deformations of the liver, such as those due to pneumoperitoneum. The accuracy results of the reconstruction method was found to be 3.7±0.8 mm in terms of Hausdorff distance. The validation therefore indicates the feasibility and accuracy of the surface reconstruction method. © 2018 IEEE.

关键词： Surface reconstruction

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colour and visual computing symposium

作者： Seyed Ali Amirshahi Stella X. Yu Norwegian Colour and Visual Computing Laboratory Norwegian University of Science and Technology (NTNU) Gjøvik Norway UC Berkeley / ICSI Berkeley CA. USA

The following topics are dealt with: image colour analysis; image classification; feature extraction; learning (artificial intelligence); image enhancement; colour vision; cameras; object detection; medical image proc... 详细信息

关键词： Painting Histograms Feature extraction Weight measurement Image color analysis visualization

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Recognition and positioning of SBCs in BIM models using a geometric vs colour consensus approach 35

Recognition and positioning of SBCs in BIM models using a ge...

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35th International symposium on Automation and Robotics in Construction and International AEC/FM Hackathon: The Future of Building Things, ISARC 2018

作者： Adán, A. Quintana, B. Prieto, S.A. 3D Visual Computing and Robotic Lab University of Castilla La Mancha Spain

This paper proposes a new approach that recognizes different kinds of small objects that are commonly seen on walls and ceilings of buildings (Figure 1). The general idea supported in this paper is that such objects, called service building components (SBCs), should be inserted into the structure of the standard existing as-is BIM models, as they are automatically generated. But identifying these small building components within the vast dataset provided by the scanner is a difficult issue not solved yet. Our approach first processes a dense coloured point cloud and extracts global geometry and colour features to identify potential SBCs. A novel consensus algorithm between geometry and colour features is the basis to efficiently recognize and calculate the position of the existing small objects in the as-is BIM model of the building. The method has been tested in real and simulated environments providing encouraging results. © ISARC 2018 - 35th International symposium on Automation and Robotics in Construction and International AEC/FM Hackathon: The Future of Building Things. All rights reserved.

关键词： Object recognition

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