3-D Shape Estimation and Image Restoration: Exploiting Defocus and Motion-Blur [Hardcover]

Paolo Favaro (Author), Stefano Soatto (Author)

Book Description

ISBN-10: 1846281768 | ISBN-13: 978-1846281761 | Publication Date: December 18, 2006 | Edition: 1st Edition.

In the areas of image processing and computer vision, there is a particular need for software that can, given an unfocused or motion-blurred image, infer the three-dimensional shape of a scene. This book describes the analytical processes that go into designing such software, delineates the options open to programmers, and presents original algorithms. Written for readers with interests in image processing and computer vision and with backgrounds in engineering, science or mathematics, this highly practical text/reference is accessible to advanced students or those with a degree that includes basic linear algebra and calculus courses.

Editorial Reviews

Review

"This book presents a framework for estimating three-dimensional (3D) shapes from defocused and motion-blurred images. The book systematically describes various problems involved in estimating 3D shapes, and provides solutions to these problems… The book is well-written, and is equipped with Matlab code that implements the estimators presented in the chapters… I recommend this book to engineers in image processing and computer vision. Readers will learn state-of-the-art methods for shape restoration." (Hsun-Hsien Chang, ACM Computing Reviews, Vol. 49 (9), September 2008)

From the Back Cover

Images contain information about the spatial properties of the scene they depict. When coupled with suitable assumptions, images can be used to infer three-dimensional information. This useful volume concentrates on motion blur and defocus, which can be exploited to infer the 3-D structure of a scene—as well as its radiance properties—and which in turn can be used to generate novel images with better quality.

3-D Shape Estimation and Image Restoration presents a coherent framework for the analysis and design of algorithms to estimate 3-D shape from defocused and motion blurred images, and to eliminate defocus and motion blur to yield "restored" images. It provides a collection of algorithms that are optimal with respect to the chosen model and estimation criterion.

Topics and Features include:

• Comprehensive introduction to guide readers through the different areas of the topic

• Basic models of image formation

• Discussion of least-squares shape from defocus

• Unifying defocus and motion blur

• Handling multiple moving objects

• Dealing with occlusions

• Appendices supply the necessary background in optimization and regularization

• www.eps.hw.ac.uk/~pf21/FavaroSoattoBook/downloads contains implementations of relevant algorithms, test data and demos.

Written for readers with interests in image processing and computer vision and with backgrounds in engineering, science or mathematics, this highly practical text/reference is accessible to advanced students or those with a degree that includes basic linear algebra and calculus courses. It can also be seen as a resource for practitioners looking to expand their knowledge in the subject.

Product Details

• Hardcover: 263 pages
• Publisher: Springer; 1st Edition. edition (December 18, 2006)
• Language: English
• ISBN-10: 1846281768
• ISBN-13: 978-1846281761
• Product Dimensions: 9.3 x 6.5 x 0.6 inches
• Shipping Weight: 1.2 pounds (View shipping rates and policies)
• Average Customer Review: 1.0 out of 5 stars  See all reviews (1 customer review)
• Amazon Best Sellers Rank: #2,075,091 in Books (See Top 100 in Books)

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Most Helpful Customer Reviews

1 of 4 people found the following review helpful:

1.0 out of 5 stars gobbledygook, January 11, 2010

By 

a reader (FL) - See all my reviews

This review is from: 3-D Shape Estimation and Image Restoration: Exploiting Defocus and Motion-Blur (Hardcover)

I have gone through Chapter 4 and this chapter makes no sense to me. If you check the code in the back of the book you will find that they use equations that are not described in the text. There are two lines of code that, if deleted, radically alter their results. It's quite a coicidence that the two lines of code are of obvious theoretical and practical importance are somehow neglected in the text. The stuff that they do describe, sounds like technobabble gobbledygook.