Super-resolution of images based on local correlations

F.M. Candocia, J.C. Principe
1999 IEEE Transactions on Neural Networks  
An adaptive two step paradigm for the superresolution of optical images is developed in this paper. The procedure locally projects image samples onto a family of kernels that are learned from image data. First, an unsupervised feature extraction is performed on local neighborhood information from a training image. These features are then used to cluster the neighborhoods into disjoint sets for which an optimal mapping relating homologous neighborhoods across scales can be learned in a
more » ... manner. A superresolved image is obtained through the convolution of a low-resolution test image with the established family of kernels. Results demonstrate the effectiveness of the approach.
doi:10.1109/72.750566 pmid:18252533 fatcat:rctlrsgd5rekpmqx75layyk65y