2012 | OriginalPaper | Chapter
Super-Resolved Free-Viewpoint Image Synthesis Using Semi-global Depth Estimation and Depth-Reliability-Based Regularization
Authors : Keita Takahashi, Takeshi Naemura
Published in: Advances in Image and Video Technology
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
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.