A Pipeline for Lenslet Light Field Quality Enhancement
This addresses quality issues in lenslet cameras for light field processing applications, but it is incremental as it combines existing methods into a pipeline.
The paper tackles the problem of artefacts in lenslet light field views by proposing a pipeline that enhances RAW image processing, applies colour correction, and uses denoising, resulting in reduced ghosting, noise, and improved colour accuracy and homogeneity across sub-aperture images.
In recent years, light fields have become a major research topic and their applications span across the entire spectrum of classical image processing. Among the different methods used to capture a light field are the lenslet cameras, such as those developed by Lytro. While these cameras give a lot of freedom to the user, they also create light field views that suffer from a number of artefacts. As a result, it is common to ignore a significant subset of these views when doing high-level light field processing. We propose a pipeline to process light field views, first with an enhanced processing of RAW images to extract subaperture images, then a colour correction process using a recent colour transfer algorithm, and finally a denoising process using a state of the art light field denoising approach. We show that our method improves the light field quality on many levels, by reducing ghosting artefacts and noise, as well as retrieving more accurate and homogeneous colours across the sub-aperture images.