Digital Rock Core Images Super Resolution via SRCNN Based on Accelerated Bicubic Interpolation

Abstract

The capability of Super Resolution Convolutional Neural Networks (SRCNN) has been proved to enhance resolution of images. We applied SRCNN to enhance digital rock core images that play an important role in analyzing rock core. In this process, we noticed that the bicubic interpolation algorithm that is the first step of SRCNN might improve the speed by adjusting the calculation strategy. We proposed an SRCNN based on accelerated bicubic interpolation and tested the performance with 2000 digital rock core images. The experiment demonstrated that the accelerated bicubic interpolation algorithm faster than improved region-based bicubic image interpolation algorithm and standard bicubic interpolation algorithm, and demonstrated the feasibility of SRCNN based on our proposed algorithm to produce higher resolution digital rock core images.