Light field images super-resolution based on sub-pixel and gradient guided

Light field contains both spatial and angular information of the scene, and has a wide range of application prospects in fields such as computer vision and computer graphics. For the problem of low spatial resolution of light field images captured by light field cameras, a super-resolution method for light field images based on sub-pixel and gradient guided was proposed in this paper. A multiple sub-pixel information extraction module was designed, which divided the sub-aperture images into four image stacks: horizontal, vertical, diagonal and anti-diagonal, and extracted the sub-pixel information of each image stack separately. Meanwhile, considering that the gradient prior can provide effective clues for predicting high-frequency details, the gradient multiple sub-pixel information of the sub-aperture images was fused in the reconstruction process. Experimental results on publicly available databases show that the peak signal-to-noise ratio and structural similarity of the proposed method not only generally outperforms existing methods in objective indexes, but also has better performance in the subjective visual effect, which the edge texture details are clearer.