Finally, Moulin considers the problem of forming radar images under a diffuse-target statistical model. His estimation approach includes application of the maximum-likelihood principle and a regularization procedure based on wavelet representations. In addition, he shows that the radar imaging problem can be seen as a problem of inference on the wavelet coefficients of an image corrupted by additive noise. The aim of this special issue is to provide a forum in which researchers from the fields of mathematics, computer science, and electrical engineering who work on problems of significance to computer vision can better understand each other. I hope that the papers included in this special issue will provide a clearer picture of the role of wavelet transforms and the principles of multiresolution analysis. I wish to thank many people for their contributions and assistance in this project: Gerhard Ritter, the Editor-in-Chief of the Journal of Mathematical Imaging and Vision, who invited me to organize this issue and who provided patient guidance; the researchers who submitted papers for consideration and others who have contributed to the explosion of growth in this area; the reviewers, who provided careful and thoughtful evaluations in a timely fashion; and, finally, from these efforts, the authors of the papers selected for publication in the special issue. Andrew Laine Guest Editor Center for Computer Vision and Visualization Department of Computer and Information Sciences University of Florida Journal of Mathematical Imaging and Vision, 3, 7-38 (1993). © Kluwer Academic Publishers. Manufactured in The Netherlands.
"synopsis" may belong to another edition of this title.
Wavelet Theory and Application Presents a collection of perspectives on wavelets and multiresolution signal analysis by authors from a variety of disciplines. This work provides a snapshot of the subject, where the principles of multiresolution analysis and the contributions of wavelet transforms are further distilled.
The development of wavelet transform has provided a wealth of new mathematical results and has made possible a common ground for researchers working in a wide variety of fields, including harmonic analysis, mathematical physics, digital signal processing, image processing, and computer vision.This book presents a wide-ranging collection of perspectives on wavelets and multiresolution signal analysis by authors from a variety of disciplines. The analysis of signals and phenomena at multiple scales of resolution remains an evolving science. Thus the contributions in this book provide a snapshot of a maturing subject, where the principles of multiresolution analysis and the contributions of wavelet transforms are further distilled. The seven chapters included in this book are grouped into three general areas: image compression techniques, mathematical models and formulation, and applications in medical imaging and targe recognition. "Wavelet Theory and Application" is an edited volume of original research.
"About this title" may belong to another edition of this title.
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Condition: New. In. Seller Inventory # ria9780792393573_new
Quantity: Over 20 available
Seller: Books Puddle, New York, NY, U.S.A.
Condition: New. pp. 140. Seller Inventory # 263091872
Seller: Majestic Books, Hounslow, United Kingdom
Condition: New. Print on Demand pp. 140 68:B&W 7 x 10 in or 254 x 178 mm Case Laminate on White w/Gloss Lam. Seller Inventory # 5804671
Quantity: 4 available
Seller: moluna, Greven, Germany
Gebunden. Condition: New. Finally, Moulin considers the problem of forming radar images under a diffuse-target statistical model. His estimation approach includes application of the maximum-likelihood principle and a regularization procedure based on wavelet representations. In addi. Seller Inventory # 5971431
Quantity: Over 20 available
Seller: Biblios, Frankfurt am main, HESSE, Germany
Condition: New. PRINT ON DEMAND pp. 140. Seller Inventory # 183091882
Seller: AHA-BUCH GmbH, Einbeck, Germany
Buch. Condition: Neu. Neuware - Finally, Moulin considers the problem of forming radar images under a diffuse-target statistical model. His estimation approach includes application of the maximum-likelihood principle and a regularization procedure based on wavelet representations. In addition, he shows that the radar imaging problem can be seen as a problem of inference on the wavelet coefficients of an image corrupted by additive noise. The aim of this special issue is to provide a forum in which researchers from the fields of mathematics, computer science, and electrical engineering who work on problems of significance to computer vision can better understand each other. I hope that the papers included in this special issue will provide a clearer picture of the role of wavelet transforms and the principles of multiresolution analysis. I wish to thank many people for their contributions and assistance in this project: Gerhard Ritter, the Editor-in-Chief of the Journal of Mathematical Imaging and Vision, who invited me to organize this issue and who provided patient guidance; the researchers who submitted papers for consideration and others who have contributed to the explosion of growth in this area; the reviewers, who provided careful and thoughtful evaluations in a timely fashion; and, finally, from these efforts, the authors of the papers selected for publication in the special issue. Andrew Laine Guest Editor Center for Computer Vision and Visualization Department of Computer and Information Sciences University of Florida Journal of Mathematical Imaging and Vision, 3, 7-38 (1993). Kluwer Academic Publishers. Manufactured in The Netherlands. Seller Inventory # 9780792393573