[go: up one dir, main page]

Skip to main content

Parallel Operator Splitting Algorithms with Application to Imaging Inverse Problems

  • Book
  • © 2023

Overview

  • Addresses both algorithmic theory and numerical experiments for image restoration
  • Presents the numerical analysis of ill condition of imaging inverse problems
  • Studies comprehensively parallel operator splitting methods for solving imaging inverse problems

Part of the book series: Advanced and Intelligent Manufacturing in China (AIMC)

  • 1124 Accesses

  • 6 Citations

This is a preview of subscription content, log in via an institution to check access.

Access this book

eBook EUR 145.51
Price includes VAT (France)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book EUR 179.34
Price includes VAT (France)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book EUR 179.34
Price includes VAT (France)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

About this book

Image denoising, image deblurring, image inpainting, super-resolution, and compressed sensing reconstruction have important application value in engineering practice, and they are also the hot frontiers in the field of image processing. This book focuses on the numerical analysis of ill condition of imaging inverse problems and the methods of solving imaging inverse problems based on operator splitting. Both algorithmic theory and numerical experiments have been addressed. The book is divided into six chapters, including preparatory knowledge, ill-condition numerical analysis and regularization method of imaging inverse problems, adaptive regularization parameter estimation, and parallel solution methods of imaging inverse problem based on operator splitting. Although the research methods in this book take image denoising, deblurring, inpainting, and compressed sensing reconstruction as examples, they can also be extended to image processing problems such as image segmentation, hyperspectral decomposition, and image compression. This book can benefit teachers and graduate students in colleges and universities, or be used as a reference for self-study or further study of image processing technology engineers.

Similar content being viewed by others

Table of contents (6 chapters)

Authors and Affiliations

  • Department of Automation, High-tech Institute of Xi'an, Xi'an, China

    Chuan He, Changhua Hu

About the authors

Chuan He is an associate professor in the High-Tech Institute of Xi’an. He has been engaged in teaching and research in image processing and navigation guidance for a long time and has a deep research in the field of image restoration. He presided over 10 scientific research projects such as National Natural Science Fund, published 20 papers, won the Excellent Doctoral Dissertation Award of Shaanxi Province, and won 3 provincial and ministerial scientific research awards. He was selected into the Special Support Program for the top young talents of Shaanxi Province and technology stars of Shaanxi Province. Besides, he is a reviewer of more than ten international journals including IEEE TIP/TNNLS/TMM. 

Chuanghua Hu received the B. Eng. and M. Eng. degrees from the High-Tech Institute of Xi’an, Xi’an, China, in 1987 and 1990, respectively, and the Ph.D. degree from the Northwestern Polytechnic University, Xi’an, China, in 1996. He is currently a Cheung Kong Professor with the High-Tech Institute of Xi’an, Shaanxi, China. He was a Visiting Scholar with the University of Duisburg, Duisburg, Germany (September 2008-December 2008). He has authored or coauthored two books and about 100 articles. His research interests include signal processing, fault diagnosis and prediction, life prognosis, and fault tolerant control.



Accessibility Information

PDF accessibility summary

This PDF does not fully comply with PDF/UA standards, but does feature limited screen reader support, described non-text content (images, graphs), bookmarks for easy navigation and searchable, selectable text. Users of assistive technologies may experience difficulty navigating or interpreting content in this document. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com.

EPUB accessibility summary

This ebook is designed with accessibility in mind, aiming to meet the ePub Accessibility 1.0 AA and WCAG 2.0 Level AA standards. Its features include described images and other non-text content, screenreader-friendly navigation and accessible math. Math is represented either as MathML, LaTeX or in images. If math is represented as image, Alt Text might not be present. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com.

Bibliographic Information

Keywords

Publish with us