Lossless Coding of Light Fields based on 4D Minimum Rate Predictors

TL;DR

This paper introduces new lossless coding schemes for 4D light fields that leverage their unique structure to achieve at least 10% bit-rate savings over existing methods.

Contribution

It presents novel encoding schemes that enhance Minimum Rate Predictors by exploiting the 4D structure of light fields for improved lossless compression.

Findings

Achieved at least 10% bit-rate reduction compared to current methods.

Demonstrated effectiveness on both traditional and challenging datasets.

Enhanced prediction algorithms tailored for 4D light field data.

Abstract

Common representations of light fields use four-dimensional data structures, where a given pixel is closely related not only to its spatial neighbours within the same view, but also to its angular neighbours, co-located in adjacent views. Such structure presents increased redundancy between pixels, when compared with regular single-view images. Then, these redundancies are exploited to obtain compressed representations of the light field, using prediction algorithms specifically tailored to estimate pixel values based on both spatial and angular references. This paper proposes new encoding schemes which take advantage of the four-dimensional light field data structures to improve the coding performance of Minimum Rate Predictors. The proposed methods expand previous research on lossless coding beyond the current state-of-the-art. The experimental results, obtained using both traditional datasets and others more challenging, show bit-rate savings no smaller than 10%, when compared with existing methods for lossless light field compression.