Sequential image completion for high-speed large-pixel number sensing

Akira Hirabayashi, Naoki Nogami, Takashi Ijiri, Laurent Condat

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

1 Citation (Scopus)


We propose an algorithm that enhances the number of pixels for high-speed camera imaging to suppress its main problem. That is, the number of pixels reduces when the number of frames per second (fps) increases. To this end, we suppose an optical setup that block-randomly selects some percent of pixels in an image. Then, the proposed algorithm reconstructs the entire image from the selected partial pixels. In this algorithm, two types of sparsity are exploited. One is within each frame and the other is induced from the similarity between adjacent frames. The latter further means not only in the image domain but also in a sparsifying transformed domain. Since the cost function we define is convex, we can find the optimal solution using a convex optimization technique with small computational cost. Simulation results show that the proposed method outperforms the standard approach for image completion by the nuclear norm minimization.

Original languageEnglish
Title of host publication2016 24th European Signal Processing Conference, EUSIPCO 2016
PublisherEuropean Signal Processing Conference, EUSIPCO
Number of pages5
ISBN (Electronic)9780992862657
Publication statusPublished - 2016 Nov 28
Externally publishedYes
Event24th European Signal Processing Conference, EUSIPCO 2016 - Budapest, Hungary
Duration: 2016 Aug 282016 Sept 2

Publication series

NameEuropean Signal Processing Conference
ISSN (Print)2219-5491


Other24th European Signal Processing Conference, EUSIPCO 2016


  • Compressed sensing
  • Convex optimization
  • High-speed camera
  • Image completion
  • Sparsity

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering


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