A simple and robust super resolution method for light field images

Light field cameras generate low-resolution images due to the tradeoff between spatial and angular resolution. Traditional light field super-resolution (LFSR) methods depend on prior knowledge of depth information. This paper presents a projection-based LFSR solution without prior information based on redefinition of the mapping function between disparity and shearing shift. Moreover, simplified variational regularization is imposed in global optimization formulation to the rendered high-resolution images. Both a synthetic dataset and a real-world dataset of light field images captured by a self-developed light field camera are used to demonstrate the state-of-the-art performance of the proposed method.