A plenoptic camera captures 4D light field information in a single photographic exposure

i.e.

2D spatial and 2D angular information. Nonetheless

the spatial resolutions of images rendered from light fields are significantly low. In addition

angular resolutions cannot meet application requirements given the limited number of viewpoints. In this paper

we present a new edge-preserved super-resolution method based on the weighted BDTV model.We apply the function of the residual errors in the edges of reconstructed images to weigh the data term in addition to different low-resolution viewpoint images. We also employ the previous BDTV model for denoising and edge preservation.Experimental results demonstrate that in terms of visual effects

the reconstruction and edge-preserving effects of the proposed method is superior to those of state-of-the-art methods. Peak signal-to-noise ratio rose by 1 dB while the measures of structural similarity in images increased by roughly 0.01.Our approach not only improves the spatial and angular resolutions of rendered images but also preserves edge information. Although the depth estimate is inaccurate

the reconstruction and preservation effects of our method remain outstanding.