Amirpour, Hadi and Pinheiro, Antonio MG and Pereira, Manuela and Ghanbari, Mohammad (2019) Reliability of the Most Common Objective Metrics for Light Field Quality Assessment. In: ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019-05-12 - 2019-05-17.
Amirpour, Hadi and Pinheiro, Antonio MG and Pereira, Manuela and Ghanbari, Mohammad (2019) Reliability of the Most Common Objective Metrics for Light Field Quality Assessment. In: ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019-05-12 - 2019-05-17.
Amirpour, Hadi and Pinheiro, Antonio MG and Pereira, Manuela and Ghanbari, Mohammad (2019) Reliability of the Most Common Objective Metrics for Light Field Quality Assessment. In: ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019-05-12 - 2019-05-17.
Abstract
Light field imaging is a promising technology for 3D computational photography. As Light Field images are represented for multiple views, their subjective evaluation is a very demanding task. Hence, identifying reliable objective quality assessment methodologies plays a very important role. In this paper six objective quality metrics; PSNR-Y, PSNR-YUV, SSIM-Y, MSSSIM-Y, FSIM-Y and HDRVDP2-Y are assessed for five state-of-the-art codecs at various bit-rates. Moreover, the metrics are computed in the linear, perceptually uniform and perceptual quantizer spaces. The results are compared against those of a subjective study and is concluded that the average FSIM-Y is the most reliable metric. The paper also introduces maps of the objective metrics to evaluate the quality dispersion among the different light field image views.
Item Type: | Conference or Workshop Item (Paper) |
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Additional Information: | Published proceedings: ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) |
Uncontrolled Keywords: | Light field; image quality assessment; objective metrics |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 25 Jul 2019 13:15 |
Last Modified: | 30 Oct 2024 17:10 |
URI: | http://repository.essex.ac.uk/id/eprint/25022 |