Approximate-DCT-derived measurement matrices for compressed sensing

Jianbin Zhou, Dajiang Zhou, Takeshi Yoshimura, Satoshi Goto

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

The paper presents an algorithm to generate a series of deterministic ternary matrices, which are compatible with the new generation of CMOS image sensor (CIS), Compressed Sensing (CS) based CIS (CS-CIS). The proposed matrices are derived from the approximate DCT, hence preserving the energy compaction property as DCT does. With the proposed 2D-zigzag trimming, the limited measurements could compact most of the energy. The experiment result shows that our proposed matrix contributes a significant improvement in image quality and bitrate saving of 5.7 dB BD-PSNR increase on average comparing with the random binary matrix used in the-state-of-art CS-CIS.

Original languageEnglish
Title of host publicationIEEE International Symposium on Circuits and Systems
Subtitle of host publicationFrom Dreams to Innovation, ISCAS 2017 - Conference Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467368520
DOIs
Publication statusPublished - 2017 Sep 25
Event50th IEEE International Symposium on Circuits and Systems, ISCAS 2017 - Baltimore, United States
Duration: 2017 May 282017 May 31

Other

Other50th IEEE International Symposium on Circuits and Systems, ISCAS 2017
CountryUnited States
CityBaltimore
Period17/5/2817/5/31

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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  • Cite this

    Zhou, J., Zhou, D., Yoshimura, T., & Goto, S. (2017). Approximate-DCT-derived measurement matrices for compressed sensing. In IEEE International Symposium on Circuits and Systems: From Dreams to Innovation, ISCAS 2017 - Conference Proceedings [8050536] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISCAS.2017.8050536