Light field (LF) image super-resolution (SR) aims at reconstructing high-resolution LF
images from their low-resolution counterparts. Although CNN-based methods have …

Light fields are vector functions that map the geometry of light rays to the corresponding
plenoptic attributes. They describe the holographic information of scenes by representing …

Recent years have witnessed the great advances of deep neural networks (DNNs) in light
field (LF) image super-resolution (SR). However, existing DNN-based LF image SR methods …

Light field (LF) imaging, as an emerging temperature measurement technique, can
simultaneously capture the intensity and direction information of radiation in the combustion …

Deep learning is progressively emerging as a vital tool for image reconstruction in light field
microscopy. The present review provides a comprehensive examination of the latest …

Light field (LF) camera can simultaneously capture the intensity and direction information of
light rays, which has been widely concerned. However, limited by the size of the imaging …

Light field (LF) imaging expands traditional imaging techniques by simultaneously capturing
the intensity and direction information of light rays, and promotes many visual applications …

The emergence of Light Field (LF) cameras has made LF imaging a popular technology in
computational photography. However, the spatial resolution of these micro-lens-based LF …

In light field image compression, facilitating random access to individual views plays a
significant role in decoding views quickly, reducing memory footprint, and decreasing the …

Light field (LF) cameras usually capture dense angular samples, but suffer from low spatial
resolution. Existing single-LF super-resolution methods struggle with textures at larger …