This book is dedicated to the unique interdisciplinary research of imagery processing, recognition and perception. The contents of this book are based on the concepts of mathematical processing, compositional analysis applied in the art and design, and psychological factors of the information perception process. The conduction of compositional analysis carried out in the course of images processing and recognition, creation of the image project solution and modeling of the conceptual space structures are considered together with the mechanism of their perception. Edited and written by a group of international experts, the practical applications for industry are covered, including the influence of internet memes on social networks and face recognition technology subject to interferences. The algorithms of perception and improving of accuracy necessary for satellite imagery recognition and complex reflection from the object are represented with the use of artificial neural networks. Not just a study in how humans recognize and perceive images, this outstanding new volume delves into how these processes are used in technology for continuously evolving industrial applications. Whether for the veteran scientist or engineer, or for the student, this is a must-have for any library.

Table of Contents:
Abstract xiii Preface xv 1 Perception of Images. Modern Trends 1 Iftikhar B. Abbasov 1.1 Visual System 1 1.2 Eye. Types of Eye Movement 10 1.3 Perception of Figures and Background 33 1.4 Space Perception 46 1.5 Visual Illusions 49 1.6 Conclusion 60 2 Image Recognition Based on Compositional Schemes 63 Victoria I. Barvenko and Natalia V. Krasnovskaya 2.1 Artistic Image 63 2.2 Classification of Features 69 2.3 Compositional Analysis of an Art Work 71 2.4 Classification by Shape, Position, Color 73 2.5 Classification According to the Content of the Scenes 76 2.6 Compositional Analysis in Iconography 80 2.7 Associative Mechanism of Analysis 83 2.8 Conclusions 86 3 Sensory and Project Images in the Design Practice 89 Anna A. Kuleshova 3.1 Sensory Image Nature 89 3.2 Language and Images Symbolics 96 3.3 Methods of Images Production in Ideas 102 3.4 Personality Image Projecting 106 3.5 Project Image 108 3.6 Conclusion 120 4 Associative Perception of Conceptual Models of Exhibition Spaces 125 Olga P. Medvedeva 4.1 Associative Modeling of the Exhibition Space Environment 125 4.2 Associative Modeling of Environmental Objects in Exhibition Spaces 134 4.3 Conclusion 141 5 Disentanglement For Discriminative Visual Recognition 143 Xiaofeng Liu 5.1 Introduction 144 5.2 Problem Statement. Deep Metric Learning Based Disentanglement for FER 149 5.3 Adversarial Training Based Disentanglement 152 5.4 Methodology. Deep Metric Learning Based Disentanglement for FER 154 5.5 Adversarial Training Based Disentanglement 159 5.6 Experiments and Analysis 162 5.7 Discussion 176 5.8 Conclusion 178 6 Development of the Toolkit to Process the Internet Memes Meant for the Modeling, Analysis, Monitoring and Management of Social Processes 189 Margarita G. Kozlova, Vladimir A. Lukianenko and Mariia S. Germanchuk 6.1 Introduction 190 6.2 Modeling of Internet Memes Distribution 193 6.3 Intellectualization of System for Processing the Internet Meme Data Flow 197 6.4 Implementation of Intellectual System for Recognition of Internet Meme Data Flow 207 6.5 Conclusion 216 7 The Use of the Mathematical Apparatus of Spatial Granulation in The Problems of Perception and Image Recognition 221 Sergey A. Butenkov, Vitaly V. Krivsha and Nataly S. Krivsha 7.1 Introduction 221 7.2 The Image Processing and Analysis Base Conceptions 222 7.3 Human Visual Perception Modeling 224 7.4 Mathematic Modeling of Different Kinds of Digital Images 227 7.5 Zadeh's Information Granulation Theory 232 7.6 Fundamentals of Spatial Granulation 235 7.7 Entropy-Preserved Granulation of Spatial Data 241 7.8 Digital Images Granulation Algorithms 243 7.9 Spatial Granulation Technique Applications 247 7.10 Conclusions 257 8 Inverse Synthetic Aperture Radars: Geometry, Signal Models and Image Reconstruction Methods 261 Andon D. Lazarov and Chavdar N. Minchev 8.1 Introduction 261 8.2 ISAR Geometry and Coordinate Transformations 263 8.3 2-D ISAR Signal Models and Reconstruction Algorithms 274 8.4 3-D ISAR Signal Models and Image Reconstruction Algorithms 296 8.5 Conclusions 323 9 Remote Sensing Imagery Spatial Resolution Enhancement 327 Sergey A. Stankevich, Iryna O. Piestova and Mykola S. Lubskyi 9.1 Introduction 328 9.2 Multiband Aerospace Imagery Informativeness 328 9.3 Equivalent Spatial Resolution of Multiband Aerospace Imagery 330 9.4 Multispectral Imagery Resolution Enhancement Based on Spectral Signatures' Identification 336 9.5 Multispectral Imagery Resolution Enhancement Using Subpixels Values Reallocation According to Land Cover Classes' Topology 341 9.6 Remote Sensing Longwave Infrared Data Spatial Resolution Enhancement 346 9.7 Issues of Objective Evaluation of Remote Sensing Imagery Actual Spatial Resolution 359 9.8 Conclusion 360 10 The Theoretical and Technological Peculiarities of Aerospace Imagery Processing and Interpretation By Means of Artificial Neural Networks 369 Oleg G. Gvozdev 10.1 Introduction 371 10.2 Peculiarities of Aerospace Imagery, Ways of its Digital Representation and Tasks Solved on It 373 10.3 Aerospace Imagery Preprocessing 390 10.4 Interpretation of Aerospace Imagery by Means of Artificial Neural Networks 406 10.5 Conclusion 436 References 438 Index 445