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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