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Recovery Algorithm for Compressive Image Sensing with Adaptive Hard Thresholding

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Book cover Multimedia and Ubiquitous Engineering

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 240))

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Abstract

Iterative hard thresholding (IHT) algorithm is one of the representative compressive sensing (CS) reconstruction algorithms. For applying to images, however, it has a problem of lacking in addressing human visual system (HVS) characteristics—its hard thresholding process treats all of coefficients in transform domain equally. To overcome the problem, this paper addresses an adaptive hard thresholding method accounting for the HVS characteristics. For this purpose, a suitable threshold level is adaptively selected for each coefficient in transform domain by utilizing the standard weighting matrix table used in JPEG together with the threshold value which is estimated over the noisy version of image. Experimental results show that the performance of the block compressive sensing with smooth projected Landweber (BCS-SPL) with the proposed adaptive hard thresholding algorithm remarkably outperforms that of the conventional BCS-SPL algorithm.

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Acknowledgments

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (No. 2011-001-7578).

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Authors and Affiliations

  1. School of Electrical and Computer Engineering Sungkyunkwan University, 300 Chunchun-dong, Jangan-gu, Suwon, Korea

    Viet Anh Nguyen & Byeungwoo Jeon

Authors
  1. Viet Anh Nguyen
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  2. Byeungwoo Jeon
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Corresponding author

Correspondence to Viet Anh Nguyen .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Seoul University of Science & and Technology (SeoulTech), Seoul, Korea, Republic of (South Korea)

    James J. (Jong Hyuk) Park

  2. Dept of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong SAR

    Joseph Kee-Yin Ng

  3. Humanitas College, Kyung Hee University, Seoul, Korea, Republic of (South Korea)

    Hwa-Young Jeong

  4. School of Computer Science and Software Engineering, Monash University, Clayton, Victoria, Australia

    Borgy Waluyo

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© 2013 Springer Science+Business Media Dordrecht(Outside the USA)

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Nguyen, V.A., Jeon, B. (2013). Recovery Algorithm for Compressive Image Sensing with Adaptive Hard Thresholding. In: Park, J., Ng, JY., Jeong, HY., Waluyo, B. (eds) Multimedia and Ubiquitous Engineering. Lecture Notes in Electrical Engineering, vol 240. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-6738-6_117

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  • DOI: https://doi.org/10.1007/978-94-007-6738-6_117

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  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-007-6737-9

  • Online ISBN: 978-94-007-6738-6

  • eBook Packages: EngineeringEngineering (R0)

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