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  • 1. Engelke, Ulrich
    et al.
    Zepernick, Hans-Jürgen
    A Framework for Optimal Region of Interest-based Quality Assessment in Wireless Imaging2010In: Journal of Electronic Imaging (JEI), ISSN 1017-9909, E-ISSN 1560-229X, Vol. 19, no 1Article in journal (Refereed)
    Abstract [en]

    Images usually exhibit regions that particularly attract the viewer's attention. These regions are typically referred to as regions-of-interest (ROI) and the underlying phenomenon in the human visual system is known as visual attention (VA). In the context of image quality one may expect that distortions occuring in the ROI are perceived as being more annoying, as compared to distortions in the background. However, VA is only seldom taken into account in existing image quality metrics. In this paper, we thus provide a VA framework to extend existing image quality metrics with a simple VA model. The performance of the framework is evaluated on three contemporary image quality metrics. We further consider the context of wireless imaging where a broad range of artifacts can be observed. To facilitate the VA based metric design, we conducted subjective experiments to both obtain a ground truth for the subjective quality of a set of test images and to identify ROI in the corresponding reference images. A methodology is further discussed to optimize the VA metrics with respect to quality prediction accuracy and generalization ability. It is shown that the quality prediction performance of the three considered metrics can be significantly improved by deploying the proposed framework.

  • 2. Engelke, Ulrich
    et al.
    Zepernick, Hans-Jürgen
    Framework for Optimal Region of Interest-based Quality Assessment in Wireless Imaging2010In: Journal of Electronic Imaging (JEI), ISSN 1017-9909, E-ISSN 1560-229X, Vol. 19, no 1Article in journal (Refereed)
    Abstract [en]

    Images usually exhibit regions that particularly attract the viewer's attention. These regions are typically referred to as regions-of-interest (ROI) and the underlying phenomenon in the human visual system is known as visual attention (VA). In the context of image quality one may expect that distortions occuring in the ROI are perceived as being more annoying, as compared to distortions in the background. However, VA is only seldom taken into account in existing image quality metrics. In this paper, we thus provide a VA framework to extend existing image quality metrics with a simple VA model. The performance of the framework is evaluated on three contemporary image quality metrics. We further consider the context of wireless imaging where a broad range of artifacts can be observed. To facilitate the VA based metric design, we conducted subjective experiments to both obtain a ground truth for the subjective quality of a set of test images and to identify ROI in the corresponding reference images. A methodology is further discussed to optimize the VA metrics with respect to quality prediction accuracy and generalization ability. It is shown that the quality prediction performance of the three considered metrics can be significantly improved by deploying the proposed framework.

  • 3.
    Iqbal, Mohammad Imran
    et al.
    Blekinge Institute of Technology, School of Engineering, Department of Electrical Engineering.
    Zepernick, Hans-Jürgen
    Blekinge Institute of Technology, School of Engineering, Department of Electrical Engineering.
    Analysis and modeling of optimal error protection for embedded codestreams2012In: Journal of Electronic Imaging (JEI), ISSN 1017-9909, E-ISSN 1560-229X, Vol. 21, no 2Article in journal (Refereed)
    Abstract [en]

    Efficient utilization of bandwidth is key to providing mobile multimedia services such as wireless imaging. As such, efficient allocation of the available parity budget for error protection of the associated codestreams is essential for ensuring quality of service. Computing the optimal parity allocation to the codestream packets may not be possible in real-time due to the huge number of ways the parity can be assigned to the codestream packets. This is particularly true for systems having limited resources, such as mobile handheld devices. As a result, it is important to provide an error-protection scheme that gives good error-protection performance while imposing low computational and memory demands on the system. We therefore analyze how different parameters such as signal-to-noise ratio and source distortion-rate function affect the optimal unequal error protection (UEP) scheme for embedded codestreams. We also propose to approximate the optimal UEP using suitable mathematical models in order to reduce the complexity that otherwise would occur with computing the optimal UEP. We investigate several models for their fitness in approximating the optimal UEP using different performance metrics. The simulation results show that most of these models provide an excellent trade-off between performance and complexity.

  • 4.
    Shahid, Muhammad
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Applied Signal Processing.
    Pandremmenou,, Katerina
    Univ Ioannina, GRC.
    Lisimachos P., Kondi
    Univ Ioannina, GRC.
    Andreas, Rossholm
    Blekinge Institute of Technology, Faculty of Engineering, Department of Applied Signal Processing.
    Lövström, Benny
    Blekinge Institute of Technology, Faculty of Engineering, Department of Applied Signal Processing.
    Perceptual quality estimation of H.264/AVC videos using reduced-reference and no-reference models2016In: Journal of Electronic Imaging (JEI), ISSN 1017-9909, E-ISSN 1560-229X, Vol. 25, no 5Article in journal (Refereed)
    Abstract [en]

    Reduced-reference (RR) and no-reference (NR) models for video quality estimation, using featuresthat account for the impact of coding artifacts, spatio-temporal complexity, and packet losses, are proposed. Thepurpose of this study is to analyze a number of potentially quality-relevant features in order to select the mostsuitable set of features for building the desired models. The proposed sets of features have not been used in theliterature and some of the features are used for the first time in this study. The features are employed by the leastabsolute shrinkage and selection operator (LASSO), which selects only the most influential of them toward per-ceptual quality. For comparison, we apply feature selection in the complete feature sets and ridge regression onthe reduced sets. The models are validated using a database of H.264/AVC encoded videos that were subjec-tively assessed for quality in an ITU-T compliant laboratory. We infer that just two features selected by RRLASSO and two bitstream-based features selected by NR LASSO are able to estimate perceptual qualitywith high accuracy, higher than that of ridge, which uses more features. The comparisons with competingworks and two full-reference metrics also verify the superiority of our models.

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