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    Front cover
    Image Fusion: Algorithms and Applications
    Copyright page
    Contents
    Preface
    List of contributors
    Chapter 1. Current trends in super-resolution image reconstruction
    1.1 Introduction
    1.2 Modelling the imaging process
    1.3 State-of-the-art SR methods
    1.4 A new robust alternative for SR reconstruction
    1.5 Comparative evaluations
    1.6 Conclusions
    Acknowledgements
    References
    Chapter 2. Image fusion through multiresolution oversampled decompositions
    Chapter 3. Multisensor and multiresolution image fusion using the linear mixing model
    Chapter 4. Image fusion schemes using ICA bases
    Chapter 5. Statistical modelling for wavelet-domain image fusion
    Chapter 6. Theory and implementation of image fusion methods based on the á trous algorithm
    Chapter 7. Bayesian methods for image fusion
    Chapter 8. Multidimensional fusion by image mosaics
    Chapter 9. Fusion of multispectral and panchromatic images as an optimisation problem
    Chapter 10. Image fusion using optimisation of statistical measurements
    Chapter 11. Fusion of edge maps using statistical approaches
    Chapter 12. Enhancement of multiple sensor images using joint image fusion and blind restoration
    Chapter 13. Empirical mode decomposition for simultaneous image enhancement and fusion
    Chapter 14. Region-based multi-focus image fusion
    Chapter 15. Image fusion techniques for non-destructive testing and remote sensing applications
    Chapter 16. Concepts of image fusion in remote sensing applications
    Chapter 17. Pixel-level image fusion metrics
    Chapter 18. Objectively adaptive image fusion
    Chapter 19. Performance evaluation of image fusion techniques
    Subject index
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    Chapter 1. Current trends in super-resolution image reconstruction - Pg. 1

    1 Current trends in super-resolution image reconstruction Antonis Katartzis and Maria Petrou Communication and Signal Processing Group, Department of Electrical and Electronic Engineering, Imperial College, London, UK Super-resolution (SR) reconstruction is a branch of image fusion for bandwidth extrapo- lation beyond the limits of traditional electronic imaging systems. This chapter describes the main principles of SR reconstruction, and provides an overview of the most represen- tative methodologies in the domain. We analyse the advantages and limitations of each set