Directional Super-Resolution by means of Coded Sampling and Guided Upsampling

We present a simple guided super-resolution technique for increasing directional resolution without reliance on depth estimation or image correspondences. Rather, it searches for best-matching multidimensional (4D or 3D) patches within the entire captured data set to compose new directional images that are consistent in both the spatial and the directional domains. We describe algorithms for guided upsampling, iterative guided upsampling, and sam- pling code estimation. Our experimental results reveal that the outcomes of existing light-field camera arrays and light- stage systems can be improved without additional hardware requirements or recording effort simply by realignment of cameras or light sources to change their sampling patterns.