An Application-Oriented Approach
Buch, Englisch, 254 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 417 g
ISBN: 978-1-4613-4692-0
Verlag: Springer US
Statistical Processing Techniques for Noisy Images presents a statistical framework to design algorithms for target detection, tracking, segmentation and classification (identification). Its main goal is to provide the reader with efficient tools for developing algorithms that solve his/her own image processing applications. In particular, such topics as hypothesis test-based detection, fast active contour segmentation and algorithm design for non-conventional imaging systems are comprehensively treated, from theoretical foundations to practical implementations. With a large number of illustrations and practical examples, this book serves as an excellent textbook or reference book for senior or graduate level courses on statistical signal/image processing, as well as a reference for researchers in related fields.
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Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Informatik Bildsignalverarbeitung
- Naturwissenschaften Physik Elektromagnetismus Quantenoptik, Nichtlineare Optik, Laserphysik
- Mathematik | Informatik Mathematik Stochastik
- Geowissenschaften Geologie GIS, Geoinformatik
- Geowissenschaften Geographie | Raumplanung Geodäsie, Kartographie, GIS, Fernerkundung
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Computer Vision
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