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Advisor(s)
Abstract(s)
State-of-the-art light field (LF) image coding solutions, usually, rely in one of two LF data representation formats: Lenslet
or 4D LF. While the Lenslet data representation is a more compact version of the LF, it requires additional camera metadata
and processing steps prior to image rendering. On the contrary, 4D LF data, consisting of a stack of sub-aperture images,
provides a more redundant representation requiring, however, minimal side information, thus facilitating image rendering.
Recently, JPEG Pleno guidelines on objective evaluation of LF image coding defined a processing chain that allows to
compare different 4D LF data codecs, aiming to facilitate codec assessment and benchmark. Thus, any codec that does not
rely on the 4D LF representation needs to undergo additional processing steps to generate an output comparable to a
reference 4D LF image. These additional processing steps may have impact on the quality of the reconstructed LF image,
especially if color subsampling format and bit depth conversions have been performed. Consequently, the influence of
these conversions needs to be carefully assessed as it may have a significant impact on a comparison between different LF
codecs.
Very few in-depth comparisons on the effects of using existing LF representation have been reported. Therefore, using the
guidelines from JPEG Pleno, this paper presents an exhaustive comparative analysis of these two LF data representation
formats in terms of LF image coding efficiency, considering different color subsampling formats and bit depths. These
comparisons are performed by testing different processing chains to encode and decode the LF images. Experimental
results have shown that, in terms of coding efficiency for different color subsampling formats, the Lenslet LF data
representation is more efficient when using YUV 4:4:4 with 10 bit/sample, while the 4D LF data representation is more
efficient when using YUV 4:2:0 with 8 bit/sample. The “best” LF data representation, in terms of coding efficiency,
depends on several factors which are extensively analyzed in this paper, such as the objective metric that is used for
comparison (e.g., average PSNR-Y or average PNSR-YUV), the type of LF content, as well as the color format.
The maximum objective quality is also determined, by evaluating the influence of each block from each processing chain
in the objective quality of the reconstructed LF image. Experimental results show that, when the 4D LF data representation
is not used the maximum achieved objective quality is lower than 50 dB, in terms of average PSNR-YUV.
Description
Keywords
Light Field Light Field Image Coding Light Field Data Representation JPEG Pleno Objective Performance Assessment
Citation
Monteiro, Ricardo & Nunes, Paulo & Rodrigues, Nuno & De Faria, Sergio. (2018). Light field image coding: objective performance assessment of Lenslet and 4D LF data representations. 13. 10.1117/12.2322713.
Publisher
SPIE