Facial Image Super Resolution Using Weighted Patch Pairs
Payman Moallem, Mohammad Mostafavi, Javad Haddadnia · International Journal of Image Graphics and Signal Processing · 2013
A challenging field in image processing and computer graphics is to have higher frequency details by super resolving facial images.Unlike similar papers in this field, this paper introduces a practical face hallucinating approach with higher quality output images.The image reconstruction was based on a set of high and low resolution image pairs.Each image is divided into defined patches with overlapped regions.A patch from a defined location is removed from the low resolution (LR) input image and is compared with the LR patches of the training images with the same location.Each defined LR patch has a defined high resolution (HR) patch.Based on the Euclidean distance comparison, each patch of every single image in the training images database receives a specific weight.This weight is transferred to its relevant HR patch identically.The sum of the gained weights for one specific location of a patch is equal to unity.The HR output image is constructed by integrating the HR hallucinated patches.