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0000−0001−8949−9597] , Aiwen Jiang 1[0000−0002−5979−7590] , Juncheng Li 2[0000−0001−7314−6754] , and Abstract. Single image dehazing is a challenging ill-posed restoration problem. Various prior-based and learning-based methods have been proposed. Most of them follow a classic atmospheric scattering model which is an elegant simplified physical model based on the assumption of singlescattering and homogeneous atmospheric medium. The formulation of haze in realistic environment is more complicated. In this paper, we propose to take its essential mechanism as "black box", and focus on learning an input-adaptive trainable end-to-end dehazing model. An U-Net like encoder-decoder deep network via progressive feature fusions has been proposed to directly learn highly nonlinear transformation function from observed hazy image to haze-free ground-truth. The proposed network is evaluated on two public image dehazing benchmarks. The experiments demonstrate that it can achieve superior performance when compared with popular state-of-the-art methods. With efficient GPU memory usage, it can satisfactorily recover ultra high definition hazed image up to 4K resolution, which is unaffordable by many deep learning based dehazing algorithms.

The figure-of-merits of ferroelectrics for transducer applications are their electromechanical coupling factor and the operable temperature range. Relaxor-PbTiO3 ferroelectric crystals show a much improved electromechanical coupling factor k33 (88~93%) compared to their ceramic counterparts (65~78%) by taking advantage of the strong anisotropy of crystals. However, only a few relaxor-PbTiO3 systems, for example Pb(In1/2Nb1/2)O3-Pb(Mg1/3Nb2/3)O3-PbTiO3, can be grown into single crystals, whose operable temperature range is limited by their rhombohedral-tetragonal phase transition temperatures (Trt: 60~120 °C). Here, we develop a templated grain-growth approach to fabricate <001>-textured Pb(In1/2Nb1/2)O3-Pb(Sc1/2Nb1/2)O3-PbTiO3 (PIN-PSN-PT) ceramics that contain a large amount of the refractory component Sc2O3, which has the ability to increase the Trt of the system. The high k33 of 85~89% and the greatly increased Trt of 160~200 °C are simultaneously achieved in the textured PIN-PSN-PT ceramics. The above merits will make textured PIN-PSN-PT ceramics an alternative to single crystals, benefiting the development of numerous advanced piezoelectric devices.

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