Abstract
Objective quality assessment of digital holograms has proven to be a challenging task. While prediction of perceptual quality of the recorded 3D content from the holographic wavefield is an open problem; perceptual quality assessment from content after rendering, requires a time-consuming rendering step and a multitude of possible viewports. In this research, we use 96 Fourier holograms of the recently released HoloDB database to evaluate the performance of well-known and state-of-the-art image quality metrics on digital holograms. We compare the reference holograms with their distorted versions: (i) before rendering on the real and imaginary parts of the quantized complex-wavefield, (ii) after converting Fourier to Fresnel holograms, (iii) after rendering, on the quantized amplitude of the reconstructed data, and (iv) after subsequently removing speckle noise using a Wiener filter. For every experimental track, the quality metric predictions are compared to the Mean Opinion Scores (MOS) gathered on a 2D screen, light field display and a holographic display. Additionally, a statistical analysis of the results and a discussion on the performance of the metrics are presented. The tests demonstrate that while for each test track a few quality metrics present a highly correlated performance compared to the multiple sets of available MOS, none of them demonstrates a consistently high-performance across all four test-tracks.
Highlights
Predicting perceived visual quality for 3D media in general is highly desired
As a first step towards designing such algorithms, we report in this paper a comprehensive analysis on the prediction performance of stateof-the-art Image Quality Metrics(IQMs), based on the subjective scores provided by the HoloDB data set
The quality metric predictions are rigorously compared to three sets of Mean Opinion Scores (MOS) which were previously obtained via subjective experiments
Summary
Predicting perceived visual quality for 3D media in general is highly desired. In this regard, objective quality evaluation of 3D content has been pursued based on the type of the utilized technology to capture the depth information plus visual parallax. Apart from data selection, conducting subjective experiments requires inventive but reproducible methodologies and scoring protocols for such plenoptic content Another issue for holographic subjective experiments arises from the fact that holographic displays with acceptable visual attributes are still rare and mostly operate under laboratory conditions, which require advanced technical skills to be properly configured. As a first step towards designing such algorithms, we report in this paper a comprehensive analysis on the prediction performance of stateof-the-art Image Quality Metrics(IQMs), based on the subjective scores provided by the HoloDB data set. We explore their strengths and weaknesses with regard to the studied holographic data and summarize their behaviour when used to compare the holograms before and after rendering.
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