The Experts below are selected from a list of 318 Experts worldwide ranked by ideXlab platform
Sabine Meunier - One of the best experts on this subject based on the ideXlab platform.
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Speech and audio loudness depending on telephone audio bandwidth and codec — A Subjective Testing approach
2014 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2014Co-Authors: Idir Edjekouane, Cyril Plapous, Catherine Quinquis, Sabine MeunierAbstract:In this paper, we propose a new approach for the Subjective assessment of the loudness of complex audio signals such as speech or music. This two-stage approach makes it possible to study the influence on loudness of the frequency bandwidth and of different kinds of codecs. In the first stage, the individual loudness function of each subject is estimated using a specific 100-point response scale. In the second stage, the subject evaluates the loudness of each processed sample, by filtering or coding/decoding, using the same scale. The loudness obtained in terms of points is then converted in loudness levels in terms of phons using the estimated individual loudness function. Results show that loudness increases with the bandwidth extension up to super-wideband. Similar behavior is observed when codecs are applied.
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speech and audio loudness depending on telephone audio bandwidth and codec a Subjective Testing approach
International Conference on Acoustics Speech and Signal Processing, 2014Co-Authors: Idir Edjekouane, Cyril Plapous, Catherine Quinquis, Sabine MeunierAbstract:In this paper, we propose a new approach for the Subjective assessment of the loudness of complex audio signals such as speech or music. This two-stage approach makes it possible to study the influence on loudness of the frequency bandwidth and of different kinds of codecs. In the first stage, the individual loudness function of each subject is estimated using a specific 100-point response scale. In the second stage, the subject evaluates the loudness of each processed sample, by filtering or coding/decoding, using the same scale. The loudness obtained in terms of points is then converted in loudness levels in terms of phons using the estimated individual loudness function. Results show that loudness increases with the bandwidth extension up to super-wideband. Similar behavior is observed when codecs are applied.
Lina J. Karam - One of the best experts on this subject based on the ideXlab platform.
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A No-Reference Texture Regularity Metric Based on Visual Saliency
IEEE Transactions on Image Processing, 2015Co-Authors: Srenivas Varadarajan, Lina J. KaramAbstract:This paper presents a no-reference perceptual metric that quantifies the degree of perceived regularity in textures. The metric is based on the similarity of visual attention (VA) of the textural primitives and the periodic spatial distribution of foveated fixation regions throughout the image. A ground-truth eye-tracking database for textures is also generated as part of this paper and is used to evaluate the performance of the most popular VA models. Using the saliency map generated by the best VA model, the proposed texture regularity metric is computed. It is shown through Subjective Testing that the proposed metric has a strong correlation with the mean opinion score for the perceived regularity of textures. The proposed texture regularity metric can be used to improve the quality and performance of many image processing applications like texture synthesis, texture compression, and content-based image retrieval.
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A reduced-reference perceptual quality metric for texture synthesis
2014 IEEE International Conference on Image Processing (ICIP), 2014Co-Authors: Srenivas Varadarajan, Lina J. KaramAbstract:This paper presents a reduced-reference quality metric that quantifies the perceptual quality of the synthesized textures. The metric is based on the change in perceived regularity between the original and the synthesized textures. The perceived regularity is quantified through a modified texture regularity metric based on visual attention. It is shown through Subjective Testing that the proposed metric has a strong correlation with the Mean Opinion Score for the fidelity of synthesized textures and outperforms the state-of-the-art full-reference quality metrics.
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A no-reference perceptual texture regularity metric
2013 IEEE International Conference on Acoustics Speech and Signal Processing, 2013Co-Authors: Srenivas Varadarajan, Lina J. KaramAbstract:This paper presents a no reference perceptual metric that quantifies the degree of regularity in textures. The metric is based on the probability of visual attention at each pixel of the texture image, similarity of visual attention of the textural primitives and the periodic spatial distribution of foveated fixation regions throughout the image. It is shown through Subjective Testing that the proposed metric has a strong correlation with the Mean Opinion Score for the regularity of textures.
Idir Edjekouane - One of the best experts on this subject based on the ideXlab platform.
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Speech and audio loudness depending on telephone audio bandwidth and codec — A Subjective Testing approach
2014 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2014Co-Authors: Idir Edjekouane, Cyril Plapous, Catherine Quinquis, Sabine MeunierAbstract:In this paper, we propose a new approach for the Subjective assessment of the loudness of complex audio signals such as speech or music. This two-stage approach makes it possible to study the influence on loudness of the frequency bandwidth and of different kinds of codecs. In the first stage, the individual loudness function of each subject is estimated using a specific 100-point response scale. In the second stage, the subject evaluates the loudness of each processed sample, by filtering or coding/decoding, using the same scale. The loudness obtained in terms of points is then converted in loudness levels in terms of phons using the estimated individual loudness function. Results show that loudness increases with the bandwidth extension up to super-wideband. Similar behavior is observed when codecs are applied.
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speech and audio loudness depending on telephone audio bandwidth and codec a Subjective Testing approach
International Conference on Acoustics Speech and Signal Processing, 2014Co-Authors: Idir Edjekouane, Cyril Plapous, Catherine Quinquis, Sabine MeunierAbstract:In this paper, we propose a new approach for the Subjective assessment of the loudness of complex audio signals such as speech or music. This two-stage approach makes it possible to study the influence on loudness of the frequency bandwidth and of different kinds of codecs. In the first stage, the individual loudness function of each subject is estimated using a specific 100-point response scale. In the second stage, the subject evaluates the loudness of each processed sample, by filtering or coding/decoding, using the same scale. The loudness obtained in terms of points is then converted in loudness levels in terms of phons using the estimated individual loudness function. Results show that loudness increases with the bandwidth extension up to super-wideband. Similar behavior is observed when codecs are applied.
Zdzislaw Papir - One of the best experts on this subject based on the ideXlab platform.
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video quality assessment Subjective Testing of entertainment scenes
IEEE Signal Processing Magazine, 2015Co-Authors: Margaret Helen Pinson, Lucjan Janowski, Zdzislaw PapirAbstract:This article describes how to perform a video quality Subjective test. For companies, these tests can greatly facilitate video product development; for universities, removing perceived barriers to conducting such tests allows expanded research opportunities. This tutorial assumes no prior knowledge and focuses on proven techniques.
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Video Quality Assessment: Subjective Testing of entertainment scenes
IEEE Signal Processing Magazine, 2015Co-Authors: Margaret Helen Pinson, Lucjan Janowski, Zdzislaw PapirAbstract:This article describes how to perform a video quality Subjective test. For companies, these tests can greatly facilitate video product development; for universities, removing perceived barriers to conducting such tests allows expanded research opportunities. This tutorial assumes no prior knowledge and focuses on proven techniques. (Certain commercial equipment, materials, and/or programs are identified in this article to adequately specify the experimental procedure. In no case does such identification imply recommendation or endorsement by the National Telecommunications and Information Administration, nor does it imply that the program or equipment identified is necessarily the best available for this application.)
Srenivas Varadarajan - One of the best experts on this subject based on the ideXlab platform.
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A No-Reference Texture Regularity Metric Based on Visual Saliency
IEEE Transactions on Image Processing, 2015Co-Authors: Srenivas Varadarajan, Lina J. KaramAbstract:This paper presents a no-reference perceptual metric that quantifies the degree of perceived regularity in textures. The metric is based on the similarity of visual attention (VA) of the textural primitives and the periodic spatial distribution of foveated fixation regions throughout the image. A ground-truth eye-tracking database for textures is also generated as part of this paper and is used to evaluate the performance of the most popular VA models. Using the saliency map generated by the best VA model, the proposed texture regularity metric is computed. It is shown through Subjective Testing that the proposed metric has a strong correlation with the mean opinion score for the perceived regularity of textures. The proposed texture regularity metric can be used to improve the quality and performance of many image processing applications like texture synthesis, texture compression, and content-based image retrieval.
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A reduced-reference perceptual quality metric for texture synthesis
2014 IEEE International Conference on Image Processing (ICIP), 2014Co-Authors: Srenivas Varadarajan, Lina J. KaramAbstract:This paper presents a reduced-reference quality metric that quantifies the perceptual quality of the synthesized textures. The metric is based on the change in perceived regularity between the original and the synthesized textures. The perceived regularity is quantified through a modified texture regularity metric based on visual attention. It is shown through Subjective Testing that the proposed metric has a strong correlation with the Mean Opinion Score for the fidelity of synthesized textures and outperforms the state-of-the-art full-reference quality metrics.
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A no-reference perceptual texture regularity metric
2013 IEEE International Conference on Acoustics Speech and Signal Processing, 2013Co-Authors: Srenivas Varadarajan, Lina J. KaramAbstract:This paper presents a no reference perceptual metric that quantifies the degree of regularity in textures. The metric is based on the probability of visual attention at each pixel of the texture image, similarity of visual attention of the textural primitives and the periodic spatial distribution of foveated fixation regions throughout the image. It is shown through Subjective Testing that the proposed metric has a strong correlation with the Mean Opinion Score for the regularity of textures.
