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Denoising of Photographic Images and Video

Fundamentals, Open Challenges and New Trends

  • Marcelo Bertalmío

Part of the Advances in Computer Vision and Pattern Recognition book series (ACVPR)

Table of contents

  1. Front Matter
    Pages i-xiv
  2. Lucio Azzari, Lucas Rodrigues Borges, Alessandro Foi
    Pages 1-36
  3. Michael Moeller, Daniel Cremers
    Pages 63-91
  4. Wangmeng Zuo, Kai Zhang, Lei Zhang
    Pages 93-123
  5. Julie Delon, Antoine Houdard
    Pages 125-149
  6. Maria Zontak, Michal Irani
    Pages 151-174
  7. A. Buades, J. L. Lisani
    Pages 175-205
  8. Tamara Seybold
    Pages 235-265
  9. John R. Isidoro, Peyman Milanfar
    Pages 267-294
  10. Gabriela Ghimpeteanu, Thomas Batard, Stacey Levine, Marcelo Bertalmío
    Pages 295-329
  11. Back Matter
    Pages 331-333

About this book

Introduction

This unique text/reference presents a detailed review of noise removal for photographs and video. An international selection of expert contributors provide their insights into the fundamental challenges that remain in the field of denoising, examining how to properly model noise in real scenarios, how to tailor denoising algorithms to these models, and how to evaluate the results in a way that is consistent with perceived image quality. The book offers comprehensive coverage from problem formulation to the evaluation of denoising methods, from historical perspectives to state-of-the-art algorithms, and from fast real-time techniques that can be implemented in-camera to powerful and computationally intensive methods for off-line processing.

Topics and features:

  • Describes the basic methods for the analysis of signal-dependent and correlated noise, and the key concepts underlying sparsity-based image denoising algorithms
  • Reviews the most successful variational approaches for image reconstruction, and introduces convolutional neural network-based denoising methods
  • Provides an overview of the use of Gaussian priors for patch-based image denoising, and examines the potential of internal denoising
  • Discusses selection and estimation strategies for patch-based video denoising, and explores how noise enters the imaging pipeline
  • Surveys the properties of real camera noise, and outlines a fast approximation of nonlocal means filtering
  • Proposes routes to improving denoising results via indirectly denoising a transform of the image, considering the right noise model and taking into account the perceived quality of the outputs

This concise and clearly written volume will be of great value to researchers and professionals working in image processing and computer vision. The book will also serve as an accessible reference for advanced undergraduate and graduate students in computer science, applied mathematics, and related fields.

Marcelo Bertalmío is a Professor in the Department of Information and Communication Technologies at Universitat Pompeu Fabra, Barcelona, Spain.

Keywords

Image Processing Noise Removal Photography Image Denoising Photo Cameras

Editors and affiliations

  1. 1.Pompeu Fabra UniversityBarcelonaSpain

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-96029-6
  • Copyright Information Springer International Publishing AG, part of Springer Nature 2018
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-96028-9
  • Online ISBN 978-3-319-96029-6
  • Series Print ISSN 2191-6586
  • Series Online ISSN 2191-6594
  • Buy this book on publisher's site
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