Computational approaches in the transfer of aesthetic values from paintings to photographs: beyond red, green and blue

Description

Preface; A Quick Tour of the Contents; Acknowledgements; Contents; Part I Image Attributes and Aesthetic Aspects; 1 The Portrait and Landscape Genres; 1.1 The Portrait Genre; 1.2 The Landscape Genre; 1.3 Concluding Remarks; References; 2 The Colour Attributes of Paintings; 2.1 Painters, Paint and Colour Systems; 2.2 Colour Spaces; 2.3 Colour Contrast; 2.3.1 Itten's Contrasts; 2.3.2 Structural Contrasts; 2.3.3 Hue and Harmony; 2.4 Concluding Remarks; References; 3 Computational Models of Colour Contrast ; 3.1 Contrast Models for Simple Images; 3.2 Contrast Models for Complex Images Preface A Quick Tour of the Contents Acknowledgements Contents Part I Image Attributes and Aesthetic Aspects 1 The Portrait and Landscape Genres 1.1 The Portrait Genre 1.2 The Landscape Genre 1.3 Concluding Remarks References 2 The Colour Attributes of Paintings 2.1 Painters, Paint and Colour Systems 2.2 Colour Spaces 2.3 Colour Contrast 2.3.1 Itten's Contrasts 2.3.2 Structural Contrasts 2.3.3 Hue and Harmony 2.4 Concluding Remarks References 3 Computational Models of Colour Contrast 3.1 Contrast Models for Simple Images 3.2 Contrast Models for Complex Images 3.3 Contrast Models for Hue ContrastReferences 4 The Geometric Attributes of Paintings 4.1 Composition in Paintings 4.1.1 The Rule of Thirds 4.1.2 Region of Interest and the Horizon 4.2 Vignetting 4.3 Concluding Remarks References Part II Transfer of Aesthetic Values 5 Global Colour Style Transfer 5.1 Global Hue, Saturation and Lightness Analysis 5.2 Hue Mapping 5.2.1 RGB to RYB Conversion 5.2.2 Dominant Hue Extraction 5.2.3 Dominant Hue Alignment and Mapping 5.3 Saturation and Lightness Mapping 5.4 Experiments and Discussion 5.5 Concluding Remarks References 6 Atmospheric Perspective Effect Transfer for Landscape Photographs6.1 Introduction 6.2 Related Work 6.3 Paintings Versus Photographs 6.3.1 Depth Planes 6.3.2 Contrast in Paintings and Photographs 6.4 Contrast Manipulation 6.4.1 Reference Selection 6.4.2 Depth-Aware Contrast Mapping 6.5 Experiments and Discussion 6.6 Concluding Remarks References 7 Regional Contrast Manipulation for Portrait Photograph Enhancement 7.1 Introduction 7.2 Related Work 7.3 Paintings Versus Photographs 7.4 Example-Based Portrait Photograph Enhancement 7.4.1 Reference Selection 7.4.2 Contrast Mapping7.5 Experiments and Discussion 7.6 Concluding Remarks References 8 Composition Improvement for Portrait Photographs 8.1 Introduction 8.2 Related Work 8.3 Proposed Composition Improvement Method 8.3.1 Graph Matching 8.3.2 Space Cropping 8.4 Experiments 8.5 Concluding Remarks References 9 Vignetting Effect Transfer 9.1 Introduction 9.2 Related Work 9.3 Vignetting Effect in Paintings 9.4 Transfer of Painter-Style Vignetting to Photographs 9.4.1 Lightness Weighting Pattern and Blending Function 9.4.2 Lightness Weighting Pattern Correction 9.4.3 Content-Aware Interpolation9.4.4 Local Contrast Restoration 9.5 Experiments and Discussion 9.6 Concluding Remarks References 10 Defining Hue Contrast 10.1 Introduction 10.2 Related Work 10.3 Defining Hue Contrast 10.4 Our Approach 10.5 Computational Details 10.6 Results and Interpretations 10.7 Evaluation Through a User Study 10.8 Concluding Remarks References 11 Interactive Local Hue Contrast Manipulation 11.1 Introduction 11.2 Related Work 11.3 Hue Manipulation Framework 11.3.1 System Overview 11.3.2 Segmentation 11.3.3 Hue Histogram Selection