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Refocusing from a plenoptic camera within seconds on a mobile phone

机译:在几秒钟内在手机上从全光摄像机重新对焦

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Refocusing a plenoptic image by digital means and after the exposure has been thoroughly studied in the last years, but few efforts have been made in the direction of real time implementation in a constrained environment such as that provided by current mobile phones and tablets. In this work we address the aforementioned challenge demonstrating that a complete focal stack, comprising 31 refocused planes from a (256 × 16)~2 plenoptic image, can be achieved within seconds by a current SoC mobile phone platform. The election of an appropriate algorithm is the key to success. In a previous work we developed an algorithm, the fast approximate 4D:3D discrete Radon transform, that performs this task with linear time complexity where others obtain quadratic or linearithmic time complexity. Moreover, that algorithm does not requires complex number transforms, trigonometric calculus nor even multiplications nor float numbers. Our algorithm has been ported to a multi core ARM chip on an off-the-shelf tablet running Android. A careful implementation exploiting parallelism at several levels has been necessary. The final implementation takes advantage of multi-threading in native code and NEON SIMD instructions. As a result our current implementation completes the refocusing task within seconds for a 16 megapixels image, much faster than previous attempts running on powerful PC platforms or dedicated hardware. The times consumed by the different stages of the digital refocusing are given and the strategies to achieve this result are discussed. Time results are given for a variety of environments within Android ecosystem, from the weaker/cheaper SoCs to the top of the line for 2013.
机译:通过数字方式重新聚焦通过数字方式和在过去几年进行彻底研究后,但在受限制的环境中的实时实施方向上已经努力,例如由当前的手机和平板电脑提供的实时实施方向。在这项工作中,我们解决了上述挑战,证明了一个完整的焦点堆叠,包括来自(256×16)〜2孔图像的31个重组平面,可以在几秒内通过当前的SoC移动电话平台实现。选择适当的算法是成功的关键。在以前的工作中,我们开发了一种算法,快速近似的4D:3D离散氡变换,它以线性时间复杂度执行此任务,其中其他人获得二次或线性时间复杂度。此外,该算法不需要复杂的数转换,三角模微积分,也不需要甚至乘法和浮点数。我们的算法已移植到运行Android的现成平板电脑上的多芯臂芯片。需要在几个级别进行仔细实施并行性。最终实现利用本机代码和霓虹灯SIMD指令中的多线程。因此,我们的当前实现在几秒钟​​内完成了1600万像素的图像,比以前在功能强大的PC平台或专用硬件上运行的尝试更快。给出了数字重键的不同阶段所消耗的时间,并讨论了实现这一结果的策略。在Android生态系统内的各种环境中给出了时间结果,从较弱/更便宜的SOC到2013年的线上的顶部。

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