International audienceImage deblurring is essential in high resolution imaging, e.g., astronomy, microscopy or computational photography. Shift-invariant blur is fully characterized by a single point-spread-function (PSF). Blurring is then modeled by a convolution, leading to efficient algorithms for blur simulation and removal that rely on fast Fourier transforms. However, in many different contexts, blur cannot be considered constant throughout the field-of-view, and thus necessitates to model variations of the PSF with the location. These models must achieve a trade-off between the accuracy that can be reached with their flexibility, and their computational efficiency. Several fast approximations of blur have been proposed in the literature. We give a unified presentation of these methods in the light of matrix decompositions of the blurring operator. We establish the connection between different computational tricks that can be found in the litterature and the physical sense of corresponding approximations in terms of equivalent PSFs, physically-based approximations being preferable. We derive an improved approximation that preserves the same desirable low complexity as other fast algorithms while reaching a minimal approximation error. Comparison of theoretical properties and empirical performances of each blur approximation suggests that the proposed general model is preferable for approximation and inversion of a known shift-variant blur
In this paper, we present the results of deploying the first test prototype of the USMART low cost underwater sensor network in sea trials in Fort William, UK, on 29/06/2018 and 03/07/2018. We demonstrate the first ever hardware implementation of the TDA-MAC protocol for data gathering in underwater acoustic sensor networks (UASNs). The results show a successful application of TDA-MAC to remote environmental monitoring, integrating a range of different sensor nodes developed by the Universities of Heriot-Watt, York, Newcastle and Edinburgh. We focus on the practical challenges and their mitigation strategies related to TDA-MAC to increase its robustness in real-world deployments, compared with theoretical and simulation-based studies. The lessons learned from the sea trials reported in this paper prompted several crucial modifications to TDA-MAC which, in turn, form a solid foundation for further work on the development of TDA-MAC based UASNs.
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