Development of a Parallel Fast Fourier Transform-Based Algorithm for Digital Hologram Reconstruction / T. R. Vuyets, V. A. Ovchinnikov

Уровень набора: (RuTPU)RU\TPU\network\4598, Advanced Materials Research, Scientific JournalОсновной Автор-лицо: Vuyets, T. R.Альтернативный автор-лицо: Ovchinnikov, V. A., specialist in the field of lightning engineering, Engineer of Tomsk Polytechnic University, 1988-, Vladislav AleksandrovichКоллективный автор (вторичный): Национальный исследовательский Томский политехнический университет (ТПУ), Институт физики высоких технологий (ИФВТ), Кафедра лазерной и световой техники (ЛиСТ)Язык: английский.Страна: .Серия: Sensors, Measurements and Non-Destructive ControlРезюме или реферат: Digital holography is a comparatively new observation method for micron-sized particles. It is based on numerical reconstruction of recorded interference fringe. Calculation processes for reconstruction are both time- and memory-intensive. The aim of this study was to develop a faster, more efficient algorithm for digital hologram reconstruction. To this purpose Central Processing Unit (CPU) and Graphics Processing Unit (GPU) programming were implemented. For the problem solving the algorithms’ run-time for both configurations was measured. The results showed that the algorithm using a GPU board is faster and more suitable for reconstruction processes. Thus, it makes possible the accomplishment of real-time analysis..Аудитория: .Тематика: электронный ресурс | труды учёных ТПУ | цифровая голография | преобразование Фурье | микроскопия | субмикроны Ресурсы он-лайн:Щелкните здесь для доступа в онлайн
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Digital holography is a comparatively new observation method for micron-sized particles. It is based on numerical reconstruction of recorded interference fringe. Calculation processes for reconstruction are both time- and memory-intensive. The aim of this study was to develop a faster, more efficient algorithm for digital hologram reconstruction. To this purpose Central Processing Unit (CPU) and Graphics Processing Unit (GPU) programming were implemented. For the problem solving the algorithms’ run-time for both configurations was measured. The results showed that the algorithm using a GPU board is faster and more suitable for reconstruction processes. Thus, it makes possible the accomplishment of real-time analysis.

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