研究生: |
廖宇新 Liao, Yu-Hsin |
---|---|
論文名稱: |
光學同調繞射顯微術之HIO與Ptychography影像重建 Hybrid Input Output and Ptychographic Reconstructions of Coherent Optical Diffraction Microscopy |
指導教授: |
傅祖怡
Fu, Tsu-Yi 黃英碩 Hwang, Ing-Shouh |
學位類別: |
碩士 Master |
系所名稱: |
物理學系 Department of Physics |
論文出版年: | 2020 |
畢業學年度: | 108 |
語文別: | 中文 |
論文頁數: | 61 |
中文關鍵詞: | 同調繞射成像術 、相位取回技術 、低能量點投影顯微鏡 、HIO演算法 、PIE演算法 |
英文關鍵詞: | coherent diffraction imaging, phase retrieval technique, low energy electron point projection microscope, Hybrid Input Output algorithm, Ptychographic Iterative Engine |
DOI URL: | http://doi.org/10.6345/NTNU202000785 |
論文種類: | 學術論文 |
相關次數: | 點閱:164 下載:27 |
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使用以單原子針為電子源的低能量點投影顯微鏡(point projection microscope, PPM in short)可收取能見度高的繞射影像。以相位取回技術重建該影像,可到達原子級解析度。這表示PPM具有在不造成輻射損害的情況,觀察二維材料、生物分子和奈米材料方面的潛力。本篇的主要工作,是架設光學同調繞射成像 (Coherent Diffraction Imaging, CDI) 之實驗系統,為正在改良中的PPM,建立一套可靠的影像重建方法。我們的系統以氦氖雷射作為發射源、以市售相機作為感測器,收取實際繞射影像進行重建,作為電腦模擬繞射成功重建後的二次確認。使用HIO(Hybrid Input-Output)演算法與PIE(Ptychographic Iterative Engine) 兩種相位取回演算法來進行影像重建。本論文應用多種數據處理的方法,得到信噪與動態空間比較高的繞射影像,成功重建針孔影像,並初步重建出生物樣品上部分精細的特徵點。
High visibilty diffraction patterns of samples can be acquired by the low energy electron point projection microscope(PPM) based on a single-atom-tip(SAT) emitter. Using the phase retrieval technique, we can obtain image with atomic resolution. This implies that PPM has the potential to observe 2D materials, biomolecules, and nanomaterials without causing radiation damage. The main purpose of this work is to establish a reliable method for PPM image reconstruction. We build our own optical coherent diffraction imaging(CDI) system with a He-Ne laser and a commercial camera. The actual diffraction image is collected and reconstructed as a second confirmation after we successfully reconstruct the computer-simulated diffraction. In the thesis, two phase retrieval algorithms: HIO (Hybrid Input-Output) algorithm and PIE (Ptychographic Iterative Engine) are applied to reconstruct images. We use several data processing methods to obtain diffraction patterns with higher signal-to-noise and dynamic range. We have successfully recovered the pinhole sample image and some fine features on the biological sample.
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