Improving resolution by image registration
CVGIP: Graphical Models and Image Processing
View interpolation for image synthesis
SIGGRAPH '93 Proceedings of the 20th annual conference on Computer graphics and interactive techniques
Example-Based Super-Resolution
IEEE Computer Graphics and Applications
Super-Resolving Compressed Video with Large Artifacts
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01
IEEE Transactions on Pattern Analysis and Machine Intelligence
Camera parameter estimation from a long image sequence by tracking markers and natural features
Systems and Computers in Japan
New Multi-baseline Stereo by Counting Interest Points
CRV '05 Proceedings of the 2nd Canadian conference on Computer and Robot Vision
Panoramic movie generation using an omnidirectional multi-camera system for telepresence
SCIA'03 Proceedings of the 13th Scandinavian conference on Image analysis
Jitter camera: high resolution video from a low resolution detector
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
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This paper describes a spatio-temporal super-resolution method using depth maps for static scenes. In the proposed method, the depth maps are used as the parameters to determine the corresponding pixels in multiple input images by assuming that intrinsic and extrinsic camera parameters are known. Because the proposed method can determine the corresponding pixels in multiple images by a one-dimensional search for the depth values without the planar assumption that is often used in the literature, spatial resolution can be increased even for complex scenes. In addition, since we can use multiple frames, temporal resolution can be increased even when large parts of the image are occluded in the adjacent frame. In experiments, the validity of the proposed method is demonstrated by generating spatio-temporal super-resolution images for both synthetic and real movies.