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MMW Image Reconstruction Combined NNSC Shrinkage Technique and PDEs Algorithm

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Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence (ICIC 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6839))

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Abstract

For the problem that a millimeter wave (MMW) image contains noise and behaves low resolution, a novel MMW image reconstruction method, combined the non-negative sparse coding shrinkage (NNSCS) technique and the partial differential equations (PDEs) algorithm (denoted by NNSCS+ PDEs), is proposed in this paper. The method of PDEs is an efficient image reconstruction technique and is easy to implement. However, MMW image is highly contaminated by much unknown noise, and the reconstruction result is not satisfied only using PDEs to process images. While the NNSCS only relies on the high-order statistical property of an image and is a self-adaptive image denoising method. Thus, combined the advantage of NNSCS and PDEs, the MMW image can be well restored. In test, a natural image is used to testify the validity of the NNSC+PDEs method, and the signal noise ratio (SNR) is used as the measure criterion of restored images. Compared with NNSCS and PDEs respectively, simulation results show that our method is indeed efficient in the task of reconstructing WWM images.

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Author information

Authors and Affiliations

  1. Department of Electronic Information Engineering, Suzhou Vocational University, Suzhou, 215104, Jiangsu, China

    Li Shang & Pin-gang Su

  2. State Key Lab of Millimeter Waves, Southeast University, Nanjing, Jiangsu, China

    Pin-gang Su

Authors
  1. Li Shang
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  2. Pin-gang Su
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Editor information

Editors and Affiliations

  1. School of Electronics and Information Engineering, Tongji University, 4800 Caoan Road, 201804, Shanghai, China

    De-Shuang Huang

  2. School of Computer and Communication Engineering, Zhengzhou University of Light Industry, No. 5, Dongfeng Road, Jinshui District, 450002, Zhengzhou, Henan, China

    Yong Gan

  3. Indian Institute of Technology Kanpur, 208016, Kanpur, India

    Phalguni Gupta

  4. Department of Biotechnology, Indian Institute of Technology Madras, 600 036, Chennai, Tamilnadu, India

    M. Michael Gromiha

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© 2012 Springer-Verlag Berlin Heidelberg

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Shang, L., Su, Pg. (2012). MMW Image Reconstruction Combined NNSC Shrinkage Technique and PDEs Algorithm. In: Huang, DS., Gan, Y., Gupta, P., Gromiha, M.M. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. ICIC 2011. Lecture Notes in Computer Science(), vol 6839. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25944-9_88

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  • DOI: https://doi.org/10.1007/978-3-642-25944-9_88

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25943-2

  • Online ISBN: 978-3-642-25944-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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