Framework for optimal region of interest-based quality assessment in wireless imaging

Ulrich Engelke; Hans-Jürgen Zepernick

doi:10.1117/1.3267097

1 January 2010 Framework for optimal region of interest-based quality assessment in wireless imaging

Ulrich Engelke, Hans-Jürgen Zepernick

Author Affiliations +

Journal of Electronic Imaging, Vol. 19, Issue 1, 011005 (January 2010). https://doi.org/10.1117/1.3267097

Abstract

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 can expect that distortions occurring in the ROI are perceived as being more annoying compared to distortions in the background. However, VA is seldom taken into account in existing image quality metrics. In this work, we 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 conduct 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.

©(2010) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Ulrich Engelke and Hans-Jürgen Zepernick "Framework for optimal region of interest-based quality assessment in wireless imaging," Journal of Electronic Imaging 19(1), 011005 (1 January 2010). https://doi.org/10.1117/1.3267097

Published: 1 January 2010

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