Image Fusion: Algorithms and ApplicationsThe growth in the use of sensor technology has led to the demand for image fusion: signal processing techniques that can combine information received from different sensors into a single composite image in an efficient and reliable manner. This book brings together classical and modern algorithms and design architectures, demonstrating through applications how these can be implemented. Image Fusion: Algorithms and Applications provides a representative collection of the recent advances in research and development in the field of image fusion, demonstrating both spatial domain and transform domain fusion methods including Bayesian methods, statistical approaches, ICA and wavelet domain techniques. It also includes valuable material on image mosaics, remote sensing applications and performance evaluation. This book will be an invaluable resource to R&D engineers, academic researchers and system developers requiring the most up-to-date and complete information on image fusion algorithms, design architectures and applications.
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Contents
| 1 | |
| 27 | |
| 67 | |
| 85 | |
Chapter 5 Statistical modelling for waveletdomain image fusion | 119 |
Chapter 6 Theory and implementation of image fusion methods based on the á trous algorithm | 139 |
Chapter 7 Bayesian methods for image fusion | 157 |
Chapter 8 Multidimensional fusion by image mosaics | 193 |
Chapter 12 Enhancement of multiple sensor images using joint image fusion and blind restoration | 299 |
Chapter 13 Empirical mode decomposition for simultaneous image enhancement and fusion | 327 |
Chapter 14 Regionbased multifocus image fusion | 343 |
Chapter 15 Image fusion techniques for nondestructive testing and remote sensing applications | 367 |
Chapter 16 Concepts of image fusion in remote sensing applications | 393 |
Chapter 17 Pixellevel image fusion metrics | 429 |
Chapter 18 Objectively adaptive image fusion | 451 |
Chapter 19 Performance evaluation of image fusion techniques | 469 |
Chapter 9 Fusion of multispectral and panchromatic images as an optimisation problem | 223 |
Chapter 10 Image fusion using optimisation of statistical measurements | 251 |
Chapter 11 Fusion of edge maps using statistical approaches | 273 |
Subject index | 493 |