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Conference

Computational Color Imaging Workshop 

About: Computational Color Imaging Workshop is an academic conference. The conference publishes majorly in the area(s): Color histogram & Color space. Over the lifetime, 138 publication(s) have been published by the conference receiving 785 citation(s).

Papers published on a yearly basis

Papers
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Book ChapterDOI
20 Apr 2011
TL;DR: The connection between the natural statistics of colour images and the ability of existing colour transfer algorithms to produce plausible results is investigated and a better understanding of the performance of different colour spaces in the context of colour transfer is provided.
Abstract: Colour transfer algorithms aim to apply a colour palette, mood or style from one image to another, operating either in a threedimensional colour space, or splitting the problem into three simpler one-dimensional problems. The latter class of algorithms simply treats each of the three dimensions independently, whether justified or not. Although they rarely introduce spatial artefacts, the quality of the results depends on how the problem was split into three sub-problems, i.e. which colour space was chosen. Generally, the assumption is made that a decorrelated colour space would perform best, as decorrelation makes the three colour channels semi-independent (decorrelation is a weaker property than independence). However, such spaces are only decorrelated for well-chosen image ensembles. For individual images, this property may not hold. In this work, the connection between the natural statistics of colour images and the ability of existing colour transfer algorithms to produce plausible results is investigated. This work aims to provide a better understanding of the performance of different colour spaces in the context of colour transfer.

63 citations

Book ChapterDOI
29 Jul 2009
TL;DR: The presented biological model allows reliable dynamic range compression with natural color constancy properties and its non-separable spatio-temporal filter enhances HDR video content processing with an added temporal constancy.
Abstract: From moonlight to bright sun shine, real world visual scenes contain a very wide range of luminance; they are said to be High Dynamic Range (HDR). Our visual system is well adapted to explore and analyze such a variable visual content. It is now possible to acquire such HDR contents with digital cameras; however it is not possible to render them all on standard displays, which have only Low Dynamic Range (LDR) capabilities. This rendering usually generates bad exposure or loss of information. It is necessary to develop locally adaptive Tone Mapping Operators (TMO) to compress a HDR content to a LDR one and keep as much information as possible. The human retina is known to perform such a task to overcome the limited range of values which can be coded by neurons. The purpose of this paper is to present a TMO inspired from the retina properties. The presented biological model allows reliable dynamic range compression with natural color constancy properties. Moreover, its non-separable spatio-temporal filter enhances HDR video content processing with an added temporal constancy.

45 citations

Book ChapterDOI
29 Jul 2009
TL;DR: A new color image difference metrics based on the hue angle algorithm that takes into account the spatial properties of the human visual system is proposed, which shows improvement in performance compared to the original metric.
Abstract: Color image difference metrics have been proposed to find differences between an original image and a modified version of it. One of these metrics is the hue angle algorithm proposed by Hong and Luo in 2002. This metric does not take into account the spatial properties of the human visual system, and could therefore miscalculate the difference between an original image and a modified version of it. Because of this we propose a new color image difference metrics based on the hue angle algorithm that takes into account the spatial properties of the human visual system. The proposed metric, which we have named SHAME (Spatial Hue Angle MEtric), have been subjected to extensive testing. The results show improvement in performance compared to the original metric proposed by Hong and Luo.

35 citations

Book ChapterDOI
29 Mar 2017
TL;DR: Results demonstrate that learned descriptors, on average, significantly outperform hand-crafted descriptors for color texture classification, however, results obtained on the individual databases show that in the case of Outex 14, that includes training and test images taken under varying illuminant conditions, hand- crafted descriptors perform better than learning descriptors.
Abstract: The paper presents a comparison between hand-crafted and learned descriptors for color texture classification. The comparison is performed on five color texture databases that include images under varying imaging conditions: scales, camera orientations, light orientations, light color temperatures, etc. Results demonstrate that learned descriptors, on average, significantly outperform hand-crafted descriptors. However, results obtained on the individual databases show that in the case of Outex 14, that includes training and test images taken under varying illuminant conditions, hand-crafted descriptors perform better than learned descriptors.

33 citations

Book ChapterDOI
03 Mar 2013
TL;DR: Results show that the method limits the visual artifacts of state-of-the-art methods and leads to a visually consistent harmonization.
Abstract: The focus of this paper is automatic color harmonization, which amounts to re-coloring an image so that the obtained color palette is more harmonious for human observers. The proposed automatic algorithm builds on the pioneering works described in [3,12] where templates of harmonious colors are defined on the hue wheel. We bring three contributions in this paper: first, saliency [9] is used to predict the most attractive visual areas and estimate a consistent harmonious template. Second, an efficient color segmentation algorithm, adapted from [4], is proposed to perform consistent color mapping. Third, a new mapping function substitutes usual color shifting method. Results show that the method limits the visual artifacts of state-of-the-art methods and leads to a visually consistent harmonization.

30 citations

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Performance
Metrics
No. of papers from the Conference in previous years
YearPapers
201925
201723
201522
201325
201119
200924