Regular
ADJUSTMENT SCALING METHODOLOGY
BLACK-BOX MODELBLURRINESS
CORNER DETECTIONCOLOUR HESSIANCOMMON COLOUR APPEARANCECOLOR DIFFERENCECOLOR SEPARATIONCOLOR TRANSFORMCOLOR IMAGE PROCESSINGCOLOR QUANTIZATIONCOLOR CONSTANCYCOLOR DISCRIMINATIONCOLOR QUALITY FOR HIGH DYNAMIC RANGE COLOR CONTRASTCAMERA IMAGE PROCESSINGCONTENT BASED ADAPTATIONCOLOR DIFFERENCE THRESHOLDCOLOR MANAGEMENTCOLOUR HARRISCOLOR ERRORCMOS SENSORCOLOR APPEARANCE MODELCONTRASTCOLOR SPACECOLOR VISION DEFICIENCYCOLOR PERCEPTIONCOLOR IMAGE PROCESSING IN SPATIAL DOMAINCOLOR DIFFERENCESCOLORCOLOR REPRODUCTIONCHROMATIC ADAPTATIONCOLOR GAMUTCOLOR SPOT DETECTIONCAMERA COLOR PROCESSINGCOLOR PREFERENCE
DISTURBANCE COMPENSATORDISCUSSIONDALTONIZATION
ERROR DIFFUSIONEDGE DETECTION
FEEDFORWARD CONTROLFULL HD|INTERMEDIATE IMAGEFREE FORM MIRRORFACE RECOGNITION
GRADIENT DOMAINGAMUT BOUNDARYGENETIC ALGORITHMGAUSSIAN FILTERSGAUSSIAN BLURGRAININESS
HALFTONINGHYPERSPECTRAL IMAGEHIGH DYNAMIC RANGE IMAGINGHUMAN VISUAL SYSTEM MODEL
IMAGE QUALITY METRICIMAGE IMPROVEMENTIMAGE DENOISINGINTERMEDIATE IMAGEILLUMINATION AND REFLECTANCE SPECTRA SEPARATION (IRSS)IMAGE QUALITYIMAGE FUSIONIILLUMINATION ESTIMATION
MEDIA RELATIVE COLORIMETRYMACHINE LEARNINGMULTI-CHANNEL PRINTINGMULTIOBJECTIVE OPTIMIZATIONMULTISPECTRALMULTI-DIMENSIONAL ERROR MINIMIZATIONMULTI-TONINGMODELINGMATERIAL APPEARANCE
NEUGEBAUER PRIMARYNEGATIVE DISTORTION
OBSERVER METAMERISMOPTICAL SYSTEM
PARTITION SCALING METHODOLOGYPRINT IMAGING PIPELINEPRIMARY SELECTIONPREDICTIVE PARAMETRIC IMAGE COMPRESSION CONTROLPACKAGINGPERCEPTUAL COLOR IMAGE COMPRESSIONPRINT QUALITYPERIODIC DISTURBANCEPREFERRED COLORPRINTINGPERCEPTUAL MATCHINGPSYCHO-VISUAL EXPERIMENTAL SETUP|PARTITION SCALING METHODOLOGYPAGE CLASSIFICATION
RECOLORING
STATISTICAL COLOR IMAGE QUALITY ANALYSISSPECTRAL REPRODUCTIONSTRUCTURE TENSORSPOT COLORSSEE-THROUGHSHADOW IMAGESKY DETECTIONSKY COLOR ENHANCEMENTSOFT PROOFINGSURVEYSPECTRAL DATA RECONSTRUCTIONSPECTRAL EDGE
THERMAL INFRAREDTRANSPARENT DISPLAYTRANSPARENT PLASTICTRANSMITTED IMAGE
ULTRA SHORT THROW PROJECTOR
VISUAL SYSTEMVISIBLEVECTOR HALFTONING
WATERMARKINGWIDE COLOR GAMUTWIENER ESTIMATION
3D PRINTING3D HALFTONING
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  8  1
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Pages 1 - 6,  © Society for Imaging Science and Technology 2017
Digital Library: EI
Published Online: January  2017
  85  6
Image
Pages 7 - 11,  © Society for Imaging Science and Technology 2017
Volume 29
Issue 18

Colour gamuts can be described as a list of vertices and a list of triangular faces connecting these vertices. This method of encoding a colour gamut is convenient for both gamut mapping and gamut volume calculation. Particularly where the vertices describe a surface that is non-convex, as in most print processes, it can be difficult to obtain a face list that produces a connected and nonoverlapping surface. Methods for obtaining a face list from characterization data were evaluated using data from a wide range of printing processes, and it was found that defining a mesh and corresponding triangulation in CMYK space gave consistent results across all the data sets.

Digital Library: EI
Published Online: January  2017
  10  3
Image
Pages 12 - 20,  © Society for Imaging Science and Technology 2017
Volume 29
Issue 18

Different reproduction devices can have different sets of reproducible colours. These sets are called gamuts. The process of transforming colours from one device (or image) gamut to another is called gamut mapping. Gamut mapping has many technical issues to be considered: the used colour space, direction and magnitude of the mapping and whether and to which extent ingamut colours should be altered. Spatially invariant algorithms treat all the pixels independently on their position in the image. Spatially variant (local) algorithms allows a better rendition but introduces the problem of artefacts and/or haloing in the resulting image. In this paper we propose a spatially variant gamut mapping algorithm that creates virtually no artefacts nor haloing in the resulting image. We start from an analysis of the Retinex algorithm and devise proper functionals to build an algorithm which tries to maintain spatial ratios in the image while mapping it into the gamut and, at the same time, avoids all drawbacks of Retinex approaches. We suggest to perform the mapping in an RGB colour space rather than one of the perceptually more homogeneous ones. Although less homogeneous, we experimentally show that RGB colour spaces actually have better hue constancy according to a certain criterion.

Digital Library: EI
Published Online: January  2017
  86  6
Image
Pages 21 - 27,  © Society for Imaging Science and Technology 2017
Volume 29
Issue 18

People with Colour Vision Deficiencies (CVDs) face notable difficulties in our society that uses colours as a tool of communication in various situations related to design, architecture, traffic, education, etc. Daltonization recolouring tools are a popular strategy in image processing to improve colour perception of people with CVDs by increasing chroma and lightness contrast between confusion colours that are difficult to discriminate for people with CVDs. However, recolouring tools often fall short in practical applicability due to not taking into account basic requirements of various colour tasks, and an insufficient assessment by real people with CVDs. In this paper, we provide guidelines for the design and evaluation of Daltonization recolouring tools to increase practicability and enable their comparison with each other. Namely, a good recolouring tool for people with CVDs (i) should preserve naturalness and originality where possible; (ii) should preserve good colour identification and/or connoted meanings of colours. (iii) should sustain colour communicability consistently throughout the workflow; (iv) should enable customization for different types and severities of CVD of individual users (i.e., it should be open for the integration of different models of the human visual system (HVS)); (v) should define the visual goal of the recolouring tool; (vi) should name the target image type(s) of the tool, e.g. photographs, information graphics, maps, charts; (vii) should account for general restrictions of the medium both in acquisition and reproduction, and should acknowledge challenges related to colour management; (viii) must be tested using real observers with CVDs; and (ix) must be tested on different types of images.

Digital Library: EI
Published Online: January  2017
  30  1
Image
Pages 28 - 35,  © Society for Imaging Science and Technology 2017
Volume 29
Issue 18

Color Vision Deficiency (CVD) leads to a reduced capability to identify chromatic edges and contrast and may cause significant problems in various color tasks like, for example, comparative color tasks. Many daltonization methods to improve color perception of color-deficient people, however, change naturalness of confusion colors, which might complicate other color tasks like, for example, connotative and denotative color tasks. Thus, we present a daltonization method focusing on the enhancement of chromatic edges and contrast while preserving the naturalness of object colors as good as possible. Our proposed method, Yoshi-II-edge, is based on a previously presented method, Yoshi-II, which projects and rotates the lost information by color-deficient observers along the direction of optimal visibility. Yoshi-II-edge limits this enhancement to chromatic edges and contrast by computing an edge map obtained from the gradient of the error image between the original and its simulation. Furthermore, we propose a threshold and dilation to influence the width of the daltonized edge. We show that the performance of this method depends on the juxtaposition of confusion colors in the image. More precisely, Yoshi-II-edge performs well in images with adjacent areas of confusion colors but performs poorly in images with non-adjacent areas of confusion colors.

Digital Library: EI
Published Online: January  2017
  48  2
Image
Pages 36 - 41,  © Society for Imaging Science and Technology 2017
Volume 29
Issue 18

The paper present a method to estimate appearance difference of two 3D objects, such as 3D prints, using an RGB camera under controlled lighting environment. It consists of three parts. Firstly, calculating image color differences after geometry alignment under different light sources. Secondly, estimating glossiness of the objects with a movable light source. And finally, psychophysical data are used to determine the parameters for estimating appearance differences of 3D prints.

Digital Library: EI
Published Online: January  2017
  15  3
Image
Pages 42 - 47,  © Society for Imaging Science and Technology 2017
Volume 29
Issue 18

This paper presents a new metric for evaluating the color perceptual smoothness of color transformations. The metric estimates three dimensional smoothness to cover the full gamut of the transform. This metric predicts any artifacts like jumps in any gradient introduced by the transformation itself. From the state of the art, three works have been found and compared for evaluating their pros and cons. Based on these previous proposals, a new metric has been developed and tested with several applications. The metric is based on the perceptual distance: CIEDE2000. The defined metric is dependent on the number of ramps and the number of colors per ramp but these two parameters can be reduced to a single one called granularity. The proposed metric has been applied on the AdobeRBG and sRGB color spaces with and without the addition of artificial artifacts and tested for a large variety of granularity values. Several basic statistics have been proposed and the root mean square seems to be a good candidate for representing the global smoothness. The metric demonstrated robustness for evaluating the global smoothness of a transform and also or detecting small jumps.

Digital Library: EI
Published Online: January  2017
  60  3
Image
Pages 48 - 59,  © Society for Imaging Science and Technology 2017
Volume 29
Issue 18

To reproduce the appearance of real world scenes, a number of color appearance models have been proposed thanks to adapted psycho-visual experiments. Most of them were designed and intended for a limited dynamic range, or address only dynamic range compression applications. However, given the increasing availability of displays with higher luminance and contrast ranges, a detailed analysis of appearance attributes is also necessary for dynamic range expansion scenarios. In this study, we propose a psycho-visual experimental setup, designed by adapting and combining the adjustment and partition scaling methodologies, which we employ for measuring perceptual colorfulness of color patches with different levels of lightness, chroma and hue. The proposed setup reduces the complexity and increases the efficiency relative to previous experimental setups and allows both expert and non-expert participants to be included. From the collected data, a modified color space is obtained and a new saturation model for dynamic range compression and expansion is derived for high dynamic range imaging.

Digital Library: EI
Published Online: January  2017
  62  1
Image
Pages 60 - 66,  © Society for Imaging Science and Technology 2017
Volume 29
Issue 18

In many medical test designs, presence of a color spot can represent existence of a disease. This presence is usually verified by observation. For these tests, knowing the color discrimination threshold is necessary for modifying the indicator spots to have color differences above the threshold. In this work, a psychophysical experiment is used to determine the color difference threshold for a veterinarian test device from IDEXX company with blue-green spots. The study was conducted in two phases, In the first phase a preliminary investigation was conducted for the ideal situation, that is having perfect circular spots without any noise or non-uniformity. Method of constant stimuli was used to present designed test images to the observers. The results were analyzed using Probit analysis method. The second phase of the study was performed with objective of studying the effects of noise, imperfect spot shapes, presence of streak and presence of spot color gradient on the color difference threshold between the background and spot colors. The same experimental and analysis method was used in both phases. The results for the ideal situation showed an average discrimination threshold of 1.27 color difference (DE00) for overall data. For the realistic situation, the noisy appearance of the image and imperfectness of the shape of the spots did not affect the threshold when observers were expecting imperfect spots. However, the presence of streak and spot gradient increased the threshold.

Digital Library: EI
Published Online: January  2017
  68  7
Image
Pages 67 - 75,  © Society for Imaging Science and Technology 2017
Volume 29
Issue 18

A 'consistent colour appearance' is hard to achieve between different substrates or display systems. A chromatic adaptation transform or substrate adjustment strategy is typically used, but for this present paper a dynamically scaled ICC Media Relative transform was utilised. A soft-proofing system with a method of adjustment was used, allowing simultaneous viewing and adjustment of a reproduction colour image relative to a reference on different simulated substrates under P2 viewing conditions. The degree of adjustment was found to be highly correlated to the image content's lightness and to lesser extent its chromaticity, and was not consistent with the complete adaptation assumed by a media-relative rendering. Other aspects of the experimental setup, including accuracy, observer strategies, and the application of soft proofing for media relative adjustments are discussed.

Digital Library: EI
Published Online: January  2017

Keywords

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