The book is organised in nine principal chapters, based on the lectures themselves, covering different domains and different aspects of the overall topic. Chapters 2-4 consider the problem as applied to the ground, air and maritime domains, respectively. Chapter 5 describes the impact of image quality (i.e. resolution, signal-to-noise ratio) on the overall target recognition performance. Chapter 6 considers the performance of different approaches to the classifier algorithm. Chapter 7 considers the improvement in performance to be gained when a target can be viewed from more than one perspective, as well as the ways in which natural systems, such as bats, perform target recognition. Such systems have benefitted from millions of years of optimisation through the process of evolution, and perform the target recognition process in an intelligent, adaptive manner. Chapter 8 considers the impact of compressive sensing, which is a relatively novel processing approach, showing that considerable economies may be made in sampling and processing due to the sparseness of the information in the target scene. Chapter 9 describes advances in change detection, including the very powerful techniques of coherent change detection. Finally, Chapter 10 looks at future challenges and directions for future research.
Introduction, Page 1 of 2
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