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Adaptive transfer of color from images to maps and visualizations / Mingguang Wu in Cartography and Geographic Information Science, Vol 49 n° 4 (July 2022)  

Public [article]  inCartography and Geographic Information Science > Vol 49 n° 4 (July 2022) . - pp 289 - 312 Titre : Adaptive transfer of color from images to maps and visualizations Type de document : Article/Communication Auteurs : Mingguang Wu, Auteur ; Yanjie Sun, Auteur ; Yaqian Li, Auteur Année de publication : 2022 Article en page(s) : pp 289 - 312 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] amélioration des couleurs [Termes IGN] couleur (rédaction cartographique) [Termes IGN] données vectorielles [Termes IGN] esthétique cartographique [Termes IGN] orthoimage couleur [Termes IGN] relation sémantique [Termes IGN] saillance [Termes IGN] visualisation cartographique [Vedettes matières IGN] Géovisualisation Résumé : (auteur) Because crafting attractive and effective colors from scratch is a high-effort and time-consuming process in map and visualization design, transferring color from an inspiration source to maps and visualizations is a promising technique for both novices and experts. To date, existing image-to-image color transfer methods suffer from ambiguities and inconsistencies; no computational approach is available to transfer color from arbitrary images to vector maps. To fill this gap, we propose a computational method that transfers color from arbitrary images to a vector map. First, we classify reference images into regions with measures of saliency. Second, we quantify the communicative quality and esthetics of colors in maps; we then transform the problem of color transfer into a dual-objective, multiple-constraint optimization problem. We also present a solution method that can create a series of optimal color suggestions and generate a communicative quality-esthetic compromise solution. We compare our method with an image-to-image method based on two sample maps and six reference images. The results indicate that our method is adaptive to mapping scales, themes, and regions. The evaluation also provides preliminary evidence that our method can achieve better communicative quality and harmony. Numéro de notice : A2022-478 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2021.1982009 Date de publication en ligne : 10/11/2021 En ligne : https://doi.org/10.1080/15230406.2021.1982009 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100826 [article]

A learning-based approach to automatically evaluate the quality of sequential color schemes for maps / Taisheng Chen in Cartography and Geographic Information Science, Vol 48 n° 5 (September 2021)  

Public [article]  inCartography and Geographic Information Science > Vol 48 n° 5 (September 2021) . - pp 377-392 Titre : A learning-based approach to automatically evaluate the quality of sequential color schemes for maps Type de document : Article/Communication Auteurs : Taisheng Chen, Auteur ; Menglin Chen, Auteur ; A - Xing Zhu, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 377-392 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Rédaction cartographique [Termes IGN] amélioration des couleurs [Termes IGN] apprentissage automatique [Termes IGN] charte de couleurs [Termes IGN] cohérence des couleurs [Termes IGN] contraste de couleurs [Termes IGN] couleur (rédaction cartographique) [Termes IGN] données d'entrainement (apprentissage automatique) [Termes IGN] palette de couleurs [Termes IGN] saturation de la couleur [Termes IGN] visualisation cartographique Résumé : (auteur) Color quality evaluation is key to judging map quality, which can improve data visualization and communication. However, most existing methods for evaluating map colors are tedious and subjective manual methods. In this paper, we study sequential color schemes, a widely used map color type and propose a learning-based approach for evaluating the color quality. The approach consists of two steps. First, we extract and characterize the cartographic factors for determining the quality of sequential color schemes, such as color order, color match, color harmony, color discrimination and color uniformity. Second, we present a model to predict the color quality based on AdaBoost, a type of ensemble learning algorithm with excellent classification performance and use these factors as input data. We conduct a case study based on 781 samples and train the AdaBoost-based model to predict the quality of sequential color schemes. To evaluate the model’s performance, we calculated the area under the receiver operating characteristic (ROC) curve (AUC). The AUC values are 0.983 and 0.977 on the training data and testing data, respectively. These results indicate that the proposed approach can be used to automatically evaluate the quality of sequential color schemes for maps, which helps mapmakers select good colors. Numéro de notice : A2021-642 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/15230406.2021.1936184 Date de publication en ligne : 29/06/2021 En ligne : https://doi.org/10.1080/15230406.2021.1936184 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98335 [article]

Toward green cartography & visualization: a semantically-enriched method of generating energy-aware color schemes for digital maps / Yangli Han in Cartography and Geographic Information Science, vol 48 n° 1 (January 2021)  

Public [article]  inCartography and Geographic Information Science > vol 48 n° 1 (January 2021) . - pp 43 - 62 Titre : Toward green cartography & visualization: a semantically-enriched method of generating energy-aware color schemes for digital maps Type de document : Article/Communication Auteurs : Yangli Han, Auteur ; Mingguang Wu, Auteur ; Robert Emmett Roth, Auteur Année de publication : 2021 Article en page(s) : pp 43 - 62 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] amélioration des couleurs [Termes IGN] cartographie pour écran mobile [Termes IGN] conception cartographique [Termes IGN] couleur (rédaction cartographique) [Termes IGN] économie d'énergie [Termes IGN] enrichissement sémantique [Termes IGN] impact sur l'environnement [Termes IGN] optimisation (mathématiques) [Termes IGN] relation sémantique [Termes IGN] téléphone intelligent [Termes IGN] visualisation cartographique [Vedettes matières IGN] Géovisualisation Résumé : (auteur) We introduce a semantically-enriched method of generating color schemes for various types of digital maps that reduces the energy consumption of the display device while preserving the quality of the original design. Energy-aware design intersects two important trends in cartography. First, as more maps are viewed today on mobile, battery life has become a central constraint influencing design. Second, there is increasing need for green computing, which encourages the efficient use of energy to limit environmental impacts. This paper focuses on one important aspect of energy-aware cartography: color design. Existing research on energy-aware color adjustment methods apply broadly to images or websites. However, the colors used in maps have more structured semantic relationships than most documents viewed on mobile devices, and efforts to account for these relationships while reducing energy consumption are limited. To fill this gap, we mathematically formalize energy-aware map-color adjustment as a constrained optimization problem: we define energy consumption as the objective function and model the preservation of semantic relationships as the search constraints. We evaluate our proposed method against a common color dimming method using four maps with different semantic relationships. The evaluation suggests that our proposed method better preserves the original color semantics. Numéro de notice : A2021-018 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2020.1827040 Date de publication en ligne : 05/11/2020 En ligne : https://doi.org/10.1080/15230406.2020.1827040 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96457 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
032-2021011	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Color image processing and applications / K.N. Plataniotis (2000)

Public Titre : Color image processing and applications Type de document : Guide/Manuel Auteurs : K.N. Plataniotis, Auteur ; A.N. Venetsanopoulos, Auteur Editeur : Berlin, Heidelberg, Vienne, New York, ... : Springer Année de publication : 2000 Importance : 353 p. Format : 17 x 24 cm ISBN/ISSN/EAN : 3-540-6695361 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] accentuation de contours [Termes IGN] amélioration des couleurs [Termes IGN] classification du maximum a posteriori [Termes IGN] classification par nuées dynamiques [Termes IGN] classification pixellaire [Termes IGN] détection de contours [Termes IGN] espace colorimétrique [Termes IGN] filtrage numérique d'image [Termes IGN] filtre adaptatif [Termes IGN] image en couleur [Termes IGN] image RVB [Termes IGN] restauration d'image [Termes IGN] segmentation fondée sur les contours [Termes IGN] segmentation par décomposition-fusion [Termes IGN] seuillage d'image [Termes IGN] traitement d'image [Termes IGN] transformation en cosinus discrète [Termes IGN] uniformisation d'histogramme Index. décimale : 35.20 Traitement d'image Résumé : (Editeur) In digital signal processing, numerous powerful algorithms, both linear and nonlinear, have been developed during the past three decades. These have given rise to tremendous progress in speech and image processing. But digital processing is not restricted to communications and information processing. It also plays a leading role in such diverse fields as measurement, automatic control, robotics, medicine, biology, and geophysics, to mention just the more important ones. The projected book series will cover the entire field of contemporary digital signal processing, ranging from theory to applications, treating linear and non-linear methods for one- and higher-dimensional signals. Note de contenu : 1. COLOR SPACES 1.1 Basics of Color Vision. 1.2 The CIE Chromaticity-basedModels. 1.3 The CIE-RGB Color Model 1.4 Gamma Correction 1.5 Linear and Non-linear RGB Color Spaces 1.6 Color Spaces Linearly Related to the RGB 1.7 The YIQ Color Space 1.8 The HSI Family of Color Models 1.9 Perceptually Uniform Color Spaces 1.10 The Munsell Color Space 1.11 The Opponent Color Space 1.12 New Trends 1.13 Color Images 1.14 Summary 2 COLOR IMAGE FILTERING 2.1 Introduction 2.2 Color Noise 2.3 Modeling Sensor Noise 2.4 Modeling Transmission Noise 2.5 Multivariate Data Ordering Schemes 2.6 A Practical Example 2.7 Vector Ordering 2.8 The Distance Measures 2.9 The Similarity Measures 2.10 Filters Based on Marginal Ordering 2.11 Filters Based on Reduced Ordering 2.12 Filters Based on Vector Ordering 2.13 Directional-based Filters 2.14 Computational Complexity 2.15 Conclusion 3. ADAPTIVE IMAGE FILTERS 3.1 Introduction 3.2 The Adaptive Fuzzy System 3.3 The Bayesian Parametric Approach 3.4 The Nonpaxametric Approach 3.5 Adaptive Morphological Filters 3.6 Simulation Studies 3.7 Conclusions 4. Color Edge Detection 4.1 Introduction 4.2 Overview Of Color Edge Detection Methodology 4.3 Vector Order Statistic Edge Operators 4.4 Difference Vector Operators 4.5 Evaluation Procedures and Results 4.6 Conclusion 5. COLOR IMAGE ENHANCEMENT AND RESTORATION 5.1 Introduction 5.2 Histogram Equalization 5.3 Color Image Restoration 5.4 Restoration Algorithms 5.5 Algorithm Formulation 5.6 Conclusions 6. Color Image Segmentation 6.1 Introduction 6.2 Pixel-based Techniques 6.2.1 Histogram Thresholding 6.2.2 Clustering 6.3 Region-based Techniques 6.3.1 Region Growing 6.3.2 Split and Merge 6.4 Edge-based Techniques 6.5 Model-based Techniques 6.5.1 The Maximum A-posteriori Method 6.5.2 The Adaptive MAP Method 6.6 Physics-based Techniques 6.7 Hybrid Techniques 6.8 Application 6.8.1 Pixel Classification 6.8.2 Seed Determination 6.8.3 Region Growing 6.8.4 Region Merging 6.8.5 Results 6.9 Conclusion 7 COLOR IMAGE COMPRESSION 7.1 Introduction 7.2 Image Compression Comparison Terminology 7.3 Image Representation for Compression Applications 7.4 Lossless Waveform-based Image Compression Techniques 7.5 Lossy Waveform-based Image Compression Techniques 7.6 Second Generation Image Compression Techniques 7.7 Perceptually Motivated Compression Techniques 7.8 Color Video Compression 7.9 Conclusion 8. EMERGING APPLICATIONS 8.1 Input Analysis Using Color Information 8.2 Shape and Color Analysis 8.2.1 Fuzzy Membership Functions 8.2.2 Aggregation Operators 8.3 Experimental Results 8.4 Conclusions Numéro de notice : 11369 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Manuel Accessibilité hors numérique : Non accessible via le SUDOC Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=46094

Color enhancement of highly correlated images : channel ratio and 'chromaticity' transformation techniques / A.R. Gillespie in Remote sensing of environment, vol 22 n° 3 (01/08/1987)  

Public [article]  inRemote sensing of environment > vol 22 n° 3 (01/08/1987) . - pp 343 - 365 Titre : Color enhancement of highly correlated images : channel ratio and 'chromaticity' transformation techniques Type de document : Article/Communication Auteurs : A.R. Gillespie, Auteur ; A.B. Kahle, Auteur ; R.E. Walker, Auteur Année de publication : 1987 Article en page(s) : pp 343 - 365 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] aberration chromatique [Termes IGN] accentuation d'image [Termes IGN] amélioration des couleurs [Termes IGN] analyse en composantes principales [Termes IGN] Californie (Etats-Unis) [Termes IGN] corrélation [Termes IGN] décorrélation [Termes IGN] image multibande Numéro de notice : A1987-348 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/0034-4257(87)90088-5 En ligne : https://doi.org/10.1016/0034-4257(87)90088-5 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=24422 [article]