Super-resolution with the Focused Plenoptic Camera Based on Examples from Nearby Micro-images

Light-field cameras have demonstrated capabilities beyond traditional cameras. They can provide users functions such as digital refocusing, changing views, and 3D scene reconstruction. Although there are a lot of advantages for light-field cameras, the resolutions of the images they rendered are not high enough for today’s user demand. To enhance the resolution of the rendered images, we are going to do super-resolution for the light-field data. There are many single image super-resolution algorithms, but the light-field super-resolution methods are still rare. In this work, we propose a super-resolution method with the focused plenoptic camera. By analyzing the image formation process of the focused plenoptic camera, we figured out a way to leverage the redundant information of the plenoptic camera to further extend the state-of-the-art example-based single image super-resolution method proposed by Freedman and Fattal to light-field. The input of our method is the raw images captures by the plenoptic camera, and the output is the super-resolved raw images. We will show that the proposed method is effective and efficient, and also retains flexibilities for plenoptic rendering.