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With the exponential enhance in computing power and broad proliferation of digital cameras, large-resolution imaging is poised to develop to be the next "killer app." The rising curiosity on this technology has manifested itself in an explosion of literature on the subject. Super-Resolution Imaging consolidates key present evaluation contributions from eminent college students and practitioners on this area and serves as a kick off point for exploration into the state-of-the-artwork inside the space. It describes the most recent in every theoretical and smart options of direct relevance to academia and business, providing a base of understanding for future progress.
Choices downloadable tools to enrich supplies found inside the book
Present advances in camera sensor technology have led to an extra and extra greater number of pixels being crammed into ever-smaller areas. This has resulted in an basic decline inside the seen high high quality of recorded content material materials, necessitating enchancment of images by way of utilizing publish-processing. Providing a snapshot of the vanguard in super-resolution imaging, this book focuses on methods and strategies to reinforce footage and video previous the capabilities of the sensors that acquired them. It covers:
Historic previous and future directions of large-resolution imaging
Regionally adaptive processing methods versus globally optimum methods
Fashionable strategies for motion estimation
Recommendations on easy methods to mix robustness
Bayesian statistical approaches
Functions in distant sensing and medicine
Smart implementations and business merchandise based mostly totally on large-resolution
The book concludes by concentrating on multidisciplinary functions of super-resolution for various fields. It covers quite a lot of large-resolution imaging implementation strategies, along with variational, perform-based, multi-channel, learning-based, regionally adaptive, and nonparametric methods. This versatile book might be utilized as the thought for short packages for engineers and scientists, or as part of graduate-diploma packages in image processing.
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