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

doi:10.1117/12.2266746

14 May 2017 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

Author Affiliations +

Proceedings Volume 10338, Thirteenth International Conference on Quality Control by Artificial Vision 2017; 103380R (2017) https://doi.org/10.1117/12.2266746
Event: The International Conference on Quality Control by Artificial Vision 2017, 2017, Tokyo, Japan

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 deblurring 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.

Citation Download Citation

Yuki Matsushita, Hiroshi Kawasaki, Teruhisa Takano, Shintaro Ono, and Katsushi Ikeuchi "Joint technique of fine object boundary recovery and foreground image deblur for video including moving objects", Proc. SPIE 10338, Thirteenth International Conference on Quality Control by Artificial Vision 2017, 103380R (14 May 2017); https://doi.org/10.1117/12.2266746

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