ABLUR:用于实时应用的基于fpga的自适应去模糊核心

Giuseppe Airò Farulla, Marco Indaco, P. Prinetto, Daniele Rolfo, Pascal Trotta
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引用次数: 1

摘要

如果相机在拍照时移动,就会产生运动模糊。现有的机械技术可以防止这种影响的发生,但它们既笨重又昂贵。例如,考虑到从事拯救和救援任务的无人驾驶飞行器(UAV),需要记录场景帧以识别要救援的人和动物。在这种情况下,设备的重量是绝对重要的,不能使用额外的硬件。在这种情况下,振动不可避免地传递到相机,并且记录的帧受到模糊的影响。然后有必要实时消除每一帧的模糊,以允许后处理算法从中提取尽可能多的信息。40多年来,许多研究人员为此目的开发了理论和算法,这些理论和算法工作得很好,但通常需要多个不同版本的输入图像,大量的计算资源,大量的执行时间或密集的参数调优。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ABLUR: An FPGA-based adaptive deblurring core for real-time applications
If a camera moves while taking a picture, motion blur is induced. There exist mechanical techniques to prevent this effect to occur, but they are cumbersome and expensive. Considering for example an Unmanned Aerial Vehicle (UAV) engaged in a save and rescue mission, where recording frames of scene to identify people and animals to rescue is required. In such cases, weight of equipments is of absolute importance, and no extra hardware can be used. In such case, vibrations are unavoidably transmitted to the camera, and recorded frames are affected by blur. It is then necessary to deblur in real-time every frame to allow post-processing algorithms to extract the largest possible amount of information from them. For more than 40 years, numerous researchers have developed theories and algorithms for this purpose, which work quite well but very often require multiple different versions of the input image, huge amount of computational resources, large execution times or intensive parameters tuning.
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