A Pipeline for Lenslet Light Field Quality Enhancement

TL;DR

This paper introduces a comprehensive pipeline for enhancing lenslet light field images by improving raw image processing, color correction, and denoising, leading to higher quality and more consistent light field views.

Contribution

It presents a novel integrated pipeline combining RAW processing, color transfer, and denoising specifically tailored for lenslet light fields, improving overall image quality.

Findings

Reduced ghosting artefacts and noise in light field views

Achieved more accurate and homogeneous colours across sub-aperture images

Enhanced overall light field quality for better high-level processing

Abstract

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.