Super-Resolution of Face Images Using Kernel PCA-Based Prior
Ayan Chakrabarti, Ambasamudram Narayanan Rajagopalan, Rama Chellappa · IEEE Transactions on Multimedia · 2007
We present a learning-based method to super-resolve face images using a kernel principal component analysis-based prior model. A prior probability is formulated based on the energy lying outside the span of principal components identified in a higher-dimensional feature space. This is used to regularize the reconstruction of the high-resolution image. We demonstrate with experiments that including higher-order correlations results in significant improvements