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A Measurement Allocation for Block Image Compressive Sensing

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Cloud Computing and Security (ICCCS 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11063))

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Abstract

In this paper, we propose a measurement allocation to reduce the blocking artifacts existing in the Block Compressive Sensing (BCS) system of image. We compute the error between each image block and its adjacent ones, and evaluate the structure complexity of each block. According to the error energy, each block is adaptively measured and reconstructed. Experimental results show that the proposed method improves the qualities of reconstructed images from both subjective and objective points of view when compared with BCS of image.

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Acknowledgement

This work was supported in part by the National Natural Science Foundation of China, under Grants nos. 61501393.

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Authors and Affiliations

  1. School of Computer and Information Technology, Xinyang Normal University, Xinyang, 464000, China

    Xiaomeng Duan, Xu Li & Ran Li

Authors
  1. Xiaomeng Duan
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  2. Xu Li
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  3. Ran Li
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Corresponding author

Correspondence to Ran Li .

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Editors and Affiliations

  1. Nanjing University of Information Science and Technology, Nanjing, China

    Xingming Sun

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

    Zhaoqing Pan

  3. Department of Computer Science, Purdue University, West Lafayette, IN, USA

    Elisa Bertino

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Duan, X., Li, X., Li, R. (2018). A Measurement Allocation for Block Image Compressive Sensing. In: Sun, X., Pan, Z., Bertino, E. (eds) Cloud Computing and Security. ICCCS 2018. Lecture Notes in Computer Science(), vol 11063. Springer, Cham. https://doi.org/10.1007/978-3-030-00006-6_10

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  • DOI: https://doi.org/10.1007/978-3-030-00006-6_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00005-9

  • Online ISBN: 978-3-030-00006-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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