Name: | Description: | Size: | Format: | |
---|---|---|---|---|
2.04 MB | Adobe PDF |
Advisor(s)
Abstract(s)
This paper proposes a novel efficient light field coding approach based on a hybrid data representation. Current state-of-the-art light field coding solutions either operate on micro-images or sub-aperture
images. Consequently, the intrinsic redundancy that exists in light field images is not fully exploited,
as is demonstrated. This novel hybrid data representation approach allows to simultaneously exploit four
types of redundancies: i) sub-aperture image intra spatial redundancy, ii) sub-aperture image inter-view
redundancy, iii) intra-micro-image redundancy, and iv) inter-micro-image redundancy between neighboring
micro-images. The proposed light field coding solution allows flexibility for several types of baselines,
by adaptively exploiting the most predominant type of redundancy on a coding block basis. To demonstrate
the efficiency of using a hybrid representation, this paper proposes a set of efficient pixel prediction methods
combined with a pseudo-video sequence coding approach, based on the HEVC standard. Experimental
results show consistent average bitrate savings when the proposed codec is compared to relevant state-ofthe-art benchmarks. For lenslet light field content, the proposed coding algorithm outperforms the HEVCbased pseudo-video sequence coding benchmark by an average bitrate savings of 23%. It is shown for the
same light field content that the proposed solution outperforms JPEG Pleno verification models MuLE and
WaSP, as these codecs are only able to achieve 11% and −14% bitrate savings over the same HEVC-based
benchmark, respectively. The performance of the proposed coding approach is also validated for light fields
with wider baselines, captured with high-density camera arrays, being able to outperform both the HEVCbased benchmark, as well as MuLE and WaSP.
Description
Keywords
Light field representation Light field image coding HEVC Pseudo-video sequence Spatial Pixel prediction Least squares prediction
Citation
R. J. S. Monteiro, N. M. M. Rodrigues, S. M. M. Faria and P. J. L. Nunes, "Light Field Image Coding Based on Hybrid Data Representation," in IEEE Access, vol. 8, pp. 115728-115744, 2020, doi: 10.1109/ACCESS.2020.3004625.
Publisher
IEEE