Enhancing Digital Zoom in Mobile Phone Cameras by Low Complexity Super-Resolution

In this paper, we present an enhancement method for improvement of digital zoom feature in mobile phone cameras. The enhancement approach is based on the state-of-the-art deep learning-based super-resolution. We introduce an input super-pixel pooling layer in the enhancement framework, that down-scales the input data without losing information, and results in a 96% complexity reduction of the enhancement framework, when compared with the baseline approach. The presented model is also capable of being trained simultaneously for several scaling factors and different levels of enhancement, without affecting the complexity of the approach.