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Image dehazing using spatially displaced sensors

机译:使用空间位移传感器进行图像去涂层

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Images of outdoor scenes are often degraded by particles and water droplets in the atmosphere. Haze, fog, and smoke are such phenomena due to atmospheric absorption and scattering. Most image dehazing (haze removal) methods proposed for the last two decades employ image enhancing or restoration approach. Different variants of local adaptive algorithms for single image dehazing are suggested. These methods are successful when a haze-free image has higher contrast compared with that of the input hazy image. Other haze removal approaches estimate a dehazed image from the observed scene by solving an objective function whose parameters are adapted to local statistics of the hazed image inside a moving window. In this presentation we propose a new dehazing algorithm that utilizes several scene images. These images are captured in such a way to be spatially shifted relatively each other. Computer simulation results are provided to illustrate the performance of the proposed algorithm for restoration of hazed images.
机译:室外场景的图像通常是通过大气中的颗粒和水滴降解。由于大气吸收和散射,雾度,雾和烟是这种现象。在过去二十年中提出的大多数图像去除(雾化去除)方法采用图像增强或恢复方法。提出了针对单图像去吸附的局部自适应算法的不同变体。当与输入朦胧图像相比,当无雾图像具有更高的对比度时,这些方法是成功的。通过求解目标函数,其参数适于在移动窗口内部的危险图像的局部统计的目标函数,其他雾霾移除方法从观察到的场景估计到观察的场景中的去噪图像。在本演示文献中,我们提出了一种新的脱水算法,该算法利用了几个场景图像。这些图像以这样的方式捕获在空间上相对偏移。提供计算机模拟结果以说明所提出的算法恢复HALED图像的性能。

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