The diverse display screen imposes significant challenges for assessing the perceptual media quality across different mobile devices. In this paper, the perceived image quality on different mobile phones is investigated. Firstly, subjective experiments for image quality evaluation are implemented on 9 popular mobile phones and a broadcast-quality monitor to evaluate the impact on perceived image quality regarding the screen resolution, screen size, image resolution, and image coding quality. Furthermore, the effect of mutual interaction between the image resolution and screen resolution is analyzed and an integrated assessment parameter is proposed to establish a device-dependent image quality assessment model. This model can be used to predict the user’s perceptual quality of the images displayed on different mobile devices. Experimental results using twofold cross-validation indicate that the proposed model can accurately estimate users’ perceived image quality on mobile devices.
Witnessing broad energy‐critical applications of barrier coverage in mobile and wireless sensor networks, emerging practical applications have recently brought a new barrier coverage model which uses sink‐based mobile sensors for covering a given barrier with the aim of prolonging the lifespan of the coverage. In the model, a set of sink stations were distributed on the plane in which each sink can emit mobile sensors with an identical radius. The task is to cover a given line barrier with the emitted mobile sensors, aiming to minimize the maximum movement of the sensors so as to prolong the shortest lifespan among the sensors in coverage. In this paper, we first devise an algorithm for optimally solving the problem based on the properties of the structures called movement parity and tangent equilibrium points between the sinks. Then based on a more sophisticated geometric property of optimum solutions, we improve the runtime to a linear runtime O(k) which attains the possibly optimum runtime of the problem for k being the number of sinks. At last, numerical experiments are carried out to demonstrate the practical performance gain of our algorithms against baselines in literature.
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