Super-Resolved Free-Viewpoint Image Synthesis Using Semi-global Depth Estimation and Depth-Reliability-Based Regularization

A method for synthesizing high-quality free-viewpoint images from a set of multi-view images is presented. First, an accurate depth map is estimated from a given target viewpoint using modified semi-global stereo matching. Then, a high-resolution image from that viewpoint is obtained through super-r...

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Bibliographic Details
Published inAdvances in Image and Video Technology Vol. 7087; pp. 22 - 35
Main Authors Takahashi, Keita, Naemura, Takeshi
Format Book Chapter
LanguageEnglish
Published Germany Springer Berlin / Heidelberg 2011
Springer Berlin Heidelberg
SeriesLecture Notes in Computer Science
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ISBN9783642253669
3642253660
ISSN0302-9743
1611-3349
DOI10.1007/978-3-642-25367-6_3

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Summary:A method for synthesizing high-quality free-viewpoint images from a set of multi-view images is presented. First, an accurate depth map is estimated from a given target viewpoint using modified semi-global stereo matching. Then, a high-resolution image from that viewpoint is obtained through super-resolution reconstruction. The depth estimation results from the first step are used for the second step. First, the depth values are used to associate pixels between the input images and the latent high-resolution image. Second, the pixel-wise reliabilities of the depth information are used for regularization to adaptively control the strength of the super-resolution reconstruction. Experimental results using real images showed the effectiveness of our method.
ISBN:9783642253669
3642253660
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-642-25367-6_3