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研究生: 李易達
Yi-Ta Lee
論文名稱: 繪圖處理器於數位全像顯微術之研究
A Study on Graphic Processing Unit Computing in Digital Holographic Microscopy
指導教授: 鄭超仁
Cheng, Chau-Jern
杜翰艷
Tu, Han-Yen
學位類別: 碩士
Master
系所名稱: 光電工程研究所
Graduate Institute of Electro-Optical Engineering
論文出版年: 2010
畢業學年度: 98
語文別: 中文
論文頁數: 88
中文關鍵詞: 繪圖處理器離軸式數位全像顯微系統平行處理數值重建相位展開
英文關鍵詞: Graphic processing unit, Off-axis digital holographic microscopy system, Parallel computing, Numerical reconstruction, Phase unwrapping
論文種類: 學術論文
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  • 在本論文中,主要探討繪圖處理器的平行運算特性及其應用於離軸式數位全像顯微系統之數值重建與相位展開,以達到即時獲得量測樣本的三維輪廓。本研究工作首先探討繪圖處理器平行處理的特性及其與串行處理運算效能之比較,並且更進一步的利用繪圖處理器於數位全像術之數值重建運算,將其演算法平行化。在重建的過程中將結合濾波處理以提高重建影像對比度,最後將所量測到樣本的相位資訊經由相位展開演算法來獲得樣本的三維資訊,並且藉由繪圖處理器高速運算的能力,以達到即時運算與顯示的效果。本研究證實了使用繪圖處理器的高速平行計算特性於數位全像顯微術具有即時重建與相位展開的潛能。內文中將提出相關模擬與實驗結果,並加以分析與說明。

    In this study, we investigate the properties of parallel computing with graphics processing unit (GPU) and its application on off-axis digital holographic microscopy (DHM). First, we study the properties of parallel computing with graphics processing unit and compare the performance to the serial computing with central processing unit (CPU). And the parallel computing with graphics processing unit can be used to integrate a filter algorithm into the numerical reconstruction calculation to get a good-quality reconstructed image and reduce the calculation time. The digital holographic microscopy equipped with the graphics processing unit can also accelerate the phase unwrapping procedure for obtaining the three-dimensional profile of a specimen in real time. This work demonstrates that high-speed parallel computing of graphic processing unit in digital holographic microscopy has great potential to perform numerical reconstruction and phase unwrapping in real time. The analytical and experimental results are presented and discussed.

    中 文 摘 要 I 英 文 摘 要 II 目 錄 III 圖目錄 V 第一章 緒論 1 1.1 數位全像顯微術之發展 1 1.2 繪圖處理器光學運算之應用 5 1.3 研究動機及挑戰 9 1.4 文獻分析 10 1.4.1 數位全像顯微系統之相位量測 10 1.4.2 繪圖處理器的應用 13 1.5 論文架構 17 第二章 數位全像顯微術與相位展開法 18 2.1 數位全像顯微術簡介 18 2.2 數位全像顯微術之記錄與重建 19 2.2.1 記錄程序 19 2.2.2 重建程序 24 2.3 相位展開法 (Phase unwrapping) 27 2.3.1 相位展開法原理與分類 27 2.3.2 最小平方相位展開法 30 2.3.3 非加權式最小平方相位展開法 35 2.3.4 加權式最小平方相位展開法 38 第三章 繪圖處理器於數位全像之平行運算 43 3.1 繪圖處理器之簡介 43 3.1.1 繪圖處理器之硬體架構 47 3.2 統一運算架構 (Compute Unified Device Architecture, CUDA) 49 3.2.1 CUDA簡介 49 3.2.2 CUDA編程模型 51 3.2.3 CUDA執行模型 54 3.2.4 CUDA記憶體模型 55 3.2.5 CPU與GPU之運算效能比較 57 3.3 數位全像重建之平行運算 59 3.3.1 平行數值重建運算 59 3.3.2 相位展開法 64 第四章 運用繪圖處理器實現即時數位全像顯微系統 66 4.1 數位全像顯微系統架構之簡介 66 4.1.1 光學架構 67 4.1.2 運算系統之硬體配置 68 4.1.3 運算系統之軟體配置 69 4.2 數位全像顯微系統之線上即時處理 70 4.2.1 光學記錄 70 4.2.2 數值重建 70 4.3 微透鏡陣列之三維輪廓量測與分析 73 4.4 CPU與GPU之運算效能比較 77 第五章 結論及未來展望 80

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