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A Novel Structure Tensor Using Nonlocal Total Variation Operator

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Advanced Multimedia and Ubiquitous Engineering (FutureTech 2017, MUE 2017)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 448))

Abstract

The structure tensor known as a second moment matrix which integrates the local data information of the image. It has been a well-established tool in the image processing field. To date a variety of nonlinear structure tensors have been emerged. Among them, the non-local structure tensors (NLSTs) is the focus of researching for the reason that it explores the spatial interactions in images. However, the performance of the existing NLST in image analysis is limited. In this paper, we propose a new structure tensor calculation method by using the nonlocal means filter to smooth the matrix-valued data. The resulting nonlocal structure tensor is effective in the orientation estimation and structural analysis of the image. Meanwhile, the nonlocal TV model based this structure tensor has been successfully applied in noise removal. Experimental results show that our model has better performance in preserving the structures, details and textures.

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Author information

Authors and Affiliations

  1. The 28th Research Institute of China Electronics Technology Group Corporation, Nanjing, 210007, China

    Yin Yu

  2. CICAEET, Nanjing University of Information Science and Technology, Nanjing, 210044, China

    Kai Ma & Yuhui Zheng

  3. College of Information Engineering, Yangzhou University, Yangzhou, 215127, China

    Jin Wang

Authors
  1. Yin Yu
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  2. Kai Ma
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  3. Yuhui Zheng
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  4. Jin Wang
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Corresponding author

Correspondence to Yin Yu .

Editor information

Editors and Affiliations

  1. Computer Science and Engineering, Seoul National University of Science and Technology, Seoul, Korea (Republic of)

    James J. (Jong Hyuk) Park

  2. School of Computing and Information Sciences, Florida International University, Miami, Florida, USA

    Shu-Ching Chen

  3. Department of Information Systems and Cyber Security, The University of Texas at San Antonio, Adelaide, Australia

    Kim-Kwang Raymond Choo

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© 2017 Springer Nature Singapore Pte Ltd.

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Yu, Y., Ma, K., Zheng, Y., Wang, J. (2017). A Novel Structure Tensor Using Nonlocal Total Variation Operator. In: Park, J., Chen, SC., Raymond Choo, KK. (eds) Advanced Multimedia and Ubiquitous Engineering. FutureTech MUE 2017 2017. Lecture Notes in Electrical Engineering, vol 448. Springer, Singapore. https://doi.org/10.1007/978-981-10-5041-1_106

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  • DOI: https://doi.org/10.1007/978-981-10-5041-1_106

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-5040-4

  • Online ISBN: 978-981-10-5041-1

  • eBook Packages: EngineeringEngineering (R0)

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