Performance Evaluation of Sparseness Significance Ranking Measure (SSRM) on Holographic Content

Ahar, Ayyoub; Birnbaum, Tobias; Blinder, David; Symeonidou, Athanasia; Schelkens, Peter

doi:10.1364/3d.2018.jtu4a.10

Cited by 7 publications

(6 citation statements)

References 5 publications

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“…While this property may be undesirable in some applications, mean-squared error based metrics have been used extensively in traditional image analysis. A suitable metric for analyzing holograms is an ongoing research problem [5,21].…”

Section: Cgh Method Hologram and Codec Parametersmentioning

confidence: 99%

Exact global motion compensation for holographic video compression

et al. 2019

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Holographic video requires impractical bitrates for storage and transmission without data compression. We introduce an end-to-end compression pipeline for compressing holographic sequences with known ground truth motion. The compression strategy employs a motion compensation algorithm based on the rotational transformation of angular spectrum. Residuals arising from the compensation step are represented using short-time Fourier transforms and quantized with uniform mid-rise quantizers whose bit depth is determined by a Lagrangian rate-distortion optimization criterion where the distortion metric is the mean squared error. Experiments uses computer generated holographic videos and we report Bjøntegaard delta peak signal to noise ratio gains of around 20 dB when compared to traditional image/video codecs.

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Section: Cgh Method Hologram and Codec Parametersmentioning

confidence: 99%

Exact global motion compensation for holographic video compression

et al. 2019

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“…Furthermore, a sparseness significance ranking measure [17] based on sparse coding and a ranking system for the magnitudes of the spatial frequency coefficients was proposed. This metric produced better results than PSNR and SSIM [18].…”

Section: Objective Quality Metricsmentioning

confidence: 99%

A new objective quality metric for phase hologram processing

Kim

2021

ETRI Journal

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Because of its convenience and compatibility with various image processing techniques, digital image representation of holograms is generally used in digital holography, and thus, quality assessment of digital holograms is an essential issue. This study proposes a new objective quality metric for digital phase hologram image processing. The proposed metric is based on a newly defined phase distortion created by taking the 2π periodicity of phase information into account. The experimental results show that the proposed metric correlates with reconstruction image quality better than the existing metric under random distortions and also works well with JPEG 2000 compression. It is expected to be broadly used in phase image processing and compression applications including phase holograms.

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“…For the current experiment, we use the mathematical measures which can directly evaluate the complex data, including Peak Signal-to-Noise Ratio (PSNR), Mean Squared Error (MSE) and its normalized form (NMSE), where the MSE is normalized by the Frobenius norm of the reference hologram. We also test our recently proposed IQM called Sparsness Significance Ranking Measure (SSRM) [56] which is native on the complex domain and showed a good compatibility for the quality evaluation of a limited set of CGHs [57]. In its original form, SSRM operates solely in Fourier domain and predicts the similarity by comparing Fourier coefficients of reference and the impaired data.…”

Section: Quality Metricsmentioning

confidence: 99%

Comprehensive Performance Analysis of Objective Quality Metrics for Digital Holography

Ahar¹,

Birnbaum²,

Chlipała³

et al. 2020

Preprint

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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 wellknown 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.

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Performance Evaluation of Sparseness Significance Ranking Measure (SSRM) on Holographic Content

Cited by 7 publications

References 5 publications

Exact global motion compensation for holographic video compression

Exact global motion compensation for holographic video compression

A new objective quality metric for phase hologram processing

Comprehensive Performance Analysis of Objective Quality Metrics for Digital Holography

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