Joint technique of fine object boundary recovery and foreground image deblur for video including moving objects

Yuki Matsushita, Hiroshi Kawasaki, Teruhisa Takano, Shintaro Ono, Katsushi Ikeuchi

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

Abstract

Capturing large scale outdoor scene by video camera becomes common for various purposes, such as city modeling, surveillance, etc., and demand of recovering high quality image from video data is increasing. Because outdoor scene includes several barriers with multiple depths and motions, e.g.., cars or fences, simply applying motion deblur technique to each frame makes some noise. Furthermore, since color is mixed with foreground and background object near occluding boundary, color separation method during debluring process is needed to restore the objects. In this paper, we propose a method to recover original boundary of foreground object from multiple blurred input images of video data. By using the refined object boundary, artifact around the border is reduced and accurate deblurring in the whole image is performed. Since both techniques are based on statistical method, quality of recovered image becomes better, if a number of input image increases. Experimental results are shown to prove that our method successfully recovers the deblurred image even if there are severe motion blur and color mixture near occluding boundary.

Original languageEnglish
Title of host publicationThirteenth International Conference on Quality Control by Artificial Vision 2017
EditorsAtsushi Yamashita, Hajime Nagahara, Kazunori Umeda
PublisherSPIE
ISBN (Electronic)9781510611214
DOIs
Publication statusPublished - Jan 1 2017
Externally publishedYes
Event13th International Conference on Quality Control by Artificial Vision, QCAV 2017 - Tokyo, Japan
Duration: May 14 2017May 16 2017

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume10338
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Other

Other13th International Conference on Quality Control by Artificial Vision, QCAV 2017
CountryJapan
CityTokyo
Period5/14/175/16/17

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All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

Cite this

Matsushita, Y., Kawasaki, H., Takano, T., Ono, S., & Ikeuchi, K. (2017). Joint technique of fine object boundary recovery and foreground image deblur for video including moving objects. In A. Yamashita, H. Nagahara, & K. Umeda (Eds.), Thirteenth International Conference on Quality Control by Artificial Vision 2017 [103380J] (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 10338). SPIE. https://doi.org/10.1117/12.2266746