High-speed imaging using CMOS image sensor with quasi pixel-wise exposure

Hajime Nagahara, Toshiki Sonoda, Kenta Endo, Yukinobu Sugiyama, Rin Ichiro Taniguchi

研究成果: 書籍/レポート タイプへの寄稿会議への寄与

16 被引用数 (Scopus)

抄録

Several recent studies in compressive video sensing have realized scene capture beyond the fundamental trade-off limit between spatial resolution and temporal resolution using random space-time sampling. However, most of these studies showed results for higher frame rate video that were produced by simulation experiments or using an optically simulated random sampling camera, because there are currently no commercially available image sensors with random exposure or sampling capabilities. We fabricated a prototype complementary metal oxide semiconductor (CMOS) image sensor with quasi pixel-wise exposure timing that can realize nonuniform space-time sampling. The prototype sensor can reset exposures independently by columns and fix these amount of exposure by rows for each 8×8 pixel block. This CMOS sensor is not fully controllable via the pixels, and has line-dependent controls, but it offers flexibility when compared with regular CMOS or charge-coupled device sensors with global or rolling shutters. We propose a method to realize pseudo-random sampling for high-speed video acquisition that uses the flexibility of the CMOS sensor. We reconstruct the high-speed video sequence from the images produced by pseudo-random sampling using an over-complete dictionary. The proposed method also removes the rolling shutter effect from the reconstructed video.

本文言語英語
ホスト出版物のタイトル2016 IEEE International Conference on Computational Photography, ICCP 2016 - Proceedings
出版社Institute of Electrical and Electronics Engineers Inc.
ISBN(電子版)9781467386234
DOI
出版ステータス出版済み - 6月 15 2016
イベント2016 IEEE International Conference on Computational Photography, ICCP 2016 - Evanston, 米国
継続期間: 5月 13 20165月 15 2016

出版物シリーズ

名前2016 IEEE International Conference on Computational Photography, ICCP 2016 - Proceedings

その他

その他2016 IEEE International Conference on Computational Photography, ICCP 2016
国/地域米国
CityEvanston
Period5/13/165/15/16

!!!All Science Journal Classification (ASJC) codes

  • メディア記述
  • 器械工学

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