Perceptual Quality of Reconstructed Medical Images on Projection-Based Light Field Displays

Embedding information reversibly in medical images for e-health

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-189157 ◽

2020 ◽

Vol 39 (6) ◽

pp. 8389-8398

Author(s):

Asra Kamili ◽

Izat Fatima ◽

Muzamil Hassan ◽

Shabir A. Parah ◽

V. Vijaya Kumar ◽

...

Keyword(s):

Medical Images ◽

Signal To Noise Ratio ◽

Perceptual Quality ◽

Embedding Capacity ◽

Electronic Patient Records ◽

Proper Diagnosis ◽

High Embedding Capacity ◽

Embedding Methods ◽

Zero Points

Embedding information in medical images is considered as one of the significant methods for safeguarding the integrity and authenticity of medical images besides providing security to electronic patient records (EPR). The conventional embedding methods deteriorate the perceptual quality of medical images making them unsuitable for proper diagnosis. To preserve the perceptual quality of medical images reversible embedding is used. The reversible embedding schemes, however, have less embedding capacity. In this work, a reversible scheme based on histogram bin shifting and RGB plane concatenation has been proposed which offers high embedding capacity as well. We have exploited the fact that medical images, unlike general images, consist of a large number of peaks and zero points that can be employed for reversibly embedding the data. Reversibility ensures that original image restoration takes place after the extraction of embedded data, which is of great importance in medical images for proper diagnosis and treatment. We have used various subjective and objective image quality metrics for analyzing the scheme. The proposed scheme has been shown to provide a Peak Signal to Noise Ratio (PSNR) value of above 56 dB for an embedding capacity of 0.58 bits per pixel (bpp). The results obtained show that the performance of scheme presented is far better in comparison to the state-of-the-art.

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Bayesian Estimation of Global and Local Variances for Improved Perceptual Quality of Fused Medical Images

2020 International Conference on Intelligent Engineering and Management (ICIEM) ◽

10.1109/iciem48762.2020.9160127 ◽

2020 ◽

Author(s):

Fayadh Alenezi

Keyword(s):

Bayesian Estimation ◽

Medical Images ◽

Perceptual Quality ◽

Global And Local

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Perceptual Quality of Light Field Images and Impact of Visualization Techniques

IEEE Transactions on Broadcasting ◽

10.1109/tbc.2020.3034445 ◽

2020 ◽

pp. 1-14

Author(s):

Pradip Paudyal ◽

Federica Battisti ◽

Patrick Le Callet ◽

Jesus Gutierrez ◽

Marco Carli

Keyword(s):

Light Field ◽

Perceptual Quality ◽

Visualization Techniques

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Singular Values Decomposition and Lifting Wavelet Transform for Speech Signal Embedding into Digital Image

Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering) ◽

10.2174/2352096511666180511151646 ◽

2019 ◽

Vol 12 (2) ◽

pp. 138-151

Author(s):

Mourad Talbi ◽

Med Salim Bouhlel

Keyword(s):

Wavelet Transform ◽

Speech Signal ◽

Signal To Noise Ratio ◽

Perceptual Quality ◽

Lifting Wavelet Transform ◽

Signal To Noise ◽

Perceptual Evaluation ◽

Lifting Wavelet ◽

Noise Ratio

Background: In this paper, we propose a secure image watermarking technique which is applied to grayscale and color images. It consists in applying the SVD (Singular Value Decomposition) in the Lifting Wavelet Transform domain for embedding a speech image (the watermark) into the host image. Methods: It also uses signature in the embedding and extraction steps. Its performance is justified by the computation of PSNR (Pick Signal to Noise Ratio), SSIM (Structural Similarity), SNR (Signal to Noise Ratio), SegSNR (Segmental SNR) and PESQ (Perceptual Evaluation Speech Quality). Results: The PSNR and SSIM are used for evaluating the perceptual quality of the watermarked image compared to the original image. The SNR, SegSNR and PESQ are used for evaluating the perceptual quality of the reconstructed or extracted speech signal compared to the original speech signal. Conclusion: The Results obtained from computation of PSNR, SSIM, SNR, SegSNR and PESQ show the performance of the proposed technique.

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Cents versus scale steps: Can we tell the difference between major and minor thirds?

Psychology of Music ◽

10.1177/0305735620987272 ◽

2021 ◽

pp. 030573562098727

Author(s):

Pedro Neto ◽

Patricia M Vanzella

Keyword(s):

Auditory Processing ◽

Perceptual Quality ◽

Chromatic Scale ◽

Major Scale ◽

Accurate Performance ◽

The Difference ◽

Scale Step ◽

Frequency Ratios ◽

Tonal Context

We report an experiment in which participants ( N = 368) were asked to differentiate between major and minor thirds. These intervals could either be formed by diatonic tones from the C major scale (tonal condition) or by a subset of tones from the chromatic scale (atonal condition). We hypothesized that in the tonal condition intervals would be perceived as a function of scale step distances, which we defined as the number of diatonic leaps between two notes of a given music scale. In the atonal condition, we hypothesized that intervals would be perceived as a function of cents. If our hypotheses were supported, we should verify a less accurate performance in the tonal condition, where scale step distances are the same between major and minor thirds. The data corroborated our hypotheses, and we suggest that acoustic measurements of intervallic distances (i.e., frequency ratios and cents) are not optimal when it comes to describing the perceptual quality of intervals in a tonal context. Finally, our research points to the possibility that, in comparison with previous models, scale steps and cents might better capture the notion of global versus local instances of auditory processing.

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