Limits on Super-Resolution and How to Break Them
IEEE Transactions on Pattern Analysis and Machine Intelligence
Theoretical Analysis on Reconstruction-Based Super-Resolution for an Arbitrary PSF
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Super resolution of images of 3D scenecs
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part II
Statistical performance analysis of super-resolution
IEEE Transactions on Image Processing
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We analyzed a light-field super-resolution problem in which, with a given set of multi-view images with a low resolution, the 3-D scene is reconstructed with a higher resolution using super-resolution (SR) reconstruction. The arrangement of the multi-view cameras is important because it determines the quality of the reconstruction. To simplify the analysis, we considered a situation in which a plane is located at a certain depth and a texture on that plane is super-resolved. We formulated the SR reconstruction process in the frequency domain, where the camera arrangement can be independently expressed as a matrix in the image formation model. We then evaluated the condition number of the matrix to quantify the quality of the SR reconstruction. We clarified that when the cameras are arranged in a regular grid, there exist singular depths in which the SR reconstruction becomes ill-posed. We also determined that this singularity can be avoided if the arrangement is randomly perturbed.