Low Bitrate Light Field Compression With Geometry and Content Consistency

Abstract

Light field imaging can simultaneously record the position and direction information of light rays; thus, digital refocusing and full depth-of-field extension — functions that are inaccessible for conventional images — can be achieved using the structural consistency of light field data. To meet the challenges of limited bandwidth and storage, such vast numbers of light field data must be compressed to a low bitrate. However, current compression solutions ignore the intrinsic consistency of light fields in pursuit of a low bitrate, thereby leading to the loss of light field capabilities. To solve this issue, this work focuses on structural consistency to achieve efficient light field compression with a low bitrate. The proposed light field compression method encodes the sparsely selected sub-aperture images (SAIs) and the disparity maps corresponding to the unselected SAIs. From the perspective of geometry consistency, the consistency of the initially estimated disparity maps is improved by using a color-guided refinement algorithm, thereby reducing the bitrate of the disparity maps. From the perspective of content consistency, the consistency of the SAI-transformed pseudo sequence is improved by the proposed content-similarity-based arrangement algorithm along with a specific prediction structure; thereby, the bitrate of the sparsely selected SAIs is reduced. The experimental results show that the proposed compression method can reduce the total bitrate while preserving good structural consistency.