Statistical Image Processing Techniques for Noisy Images : An Application-Oriented Approach
Overview
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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Details
- ISBN-13: 9781461346920
- ISBN-10: 1461346924
- Publisher: Springer
- Publish Date: November 2013
- Dimensions: 9.21 x 6.14 x 0.57 inches
- Shipping Weight: 0.85 pounds
- Page Count: 254
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