[Paper] Object Tracking and Image Restoration from Multi-Frame Images Captured in a Dark Environment

We show a method of realizing object tracking and image restoration in the dark in which target motion and a reference image are simultaneously estimated using a Bayesian framework. To avoid being trapped in a local minimum in the gradient calculation, a broader search is performed by calculating di...

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Bibliographic Details
Published inITE TRANSACTIONS ON MEDIA TECHNOLOGY AND APPLICATIONS Vol. 2; no. 2; pp. 176 - 184
Main Authors Kuroda, Hayato, Komuro, Takashi
Format Journal Article
LanguageEnglish
Published The Institute of Image Information and Television Engineers 2014
Subjects
Bayesian estimation
image deblurring
image synthesis
noise reduction
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ISSN2186-7364
2186-7364
DOI10.3169/mta.2.176

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Summary:We show a method of realizing object tracking and image restoration in the dark in which target motion and a reference image are simultaneously estimated using a Bayesian framework. To avoid being trapped in a local minimum in the gradient calculation, a broader search is performed by calculating differences after applying a strong low-pass filter to input images. Deblurring is performed using the motion parameters estimated from the blurred images. As a result, we realized object tracking and image restoration from simulated video images with an SNR of up to -6 dB, and real video images captured in a dark environment of less than 0.05 lx illuminance at the subject surface. In addition, we examined the optimal frame rate for image restoration and we found that a higher frame rate was better under relatively little noise while a lower frame rate was better under much noise.
ISSN:2186-7364
2186-7364
DOI:10.3169/mta.2.176