【摘要】：在干涉儀圖像數(shù)據(jù)處理過程中,目前采用的多行平均圖像處理算法會引入較大隨機誤差,且當(dāng)CCD相機與狹縫之間存在小轉(zhuǎn)角時,會引入較大系統(tǒng)誤差。本文主要探究利用主成分分析(PCA)算法處理空間干涉儀圖像的可行性與優(yōu)勢。利用MATLAB模擬空間干涉儀圖像,并加入隨機噪聲和圖像旋轉(zhuǎn),利用PCA方法和多行平均算法處理數(shù)據(jù),比較兩種算法的得到的結(jié)果誤差大小。并設(shè)計CCD相機小轉(zhuǎn)角實驗和干涉圖像弱信號實驗,評估PCA算法在數(shù)據(jù)處理過程中糾正CCD相機小轉(zhuǎn)角和重建弱信號圖像中的效果。理論和實驗均證明,PCA算法較目前多行平均算法,能更有效地降低噪聲,分析弱信號圖像及糾正CCD相機小轉(zhuǎn)角,消除其帶來的系統(tǒng)誤差。
[Abstract]:In the process of interferometer image data processing, the current multi-line average image processing algorithm will introduce a large random error, and when there is a small angle between the CCD camera and the slit, a large system error will be introduced. This paper mainly explores the feasibility and advantages of using principal component analysis (PCA) algorithm to process spatial interferometer images. The spatial interferometer image is simulated by MATLAB, random noise and image rotation are added, and the data are processed by PCA method and multi-line average algorithm, and the error between the two algorithms is compared. The small angle experiment of CCD camera and the weak signal experiment of interference image are designed to evaluate the effect of PCA algorithm in correcting the small angle of CCD camera and reconstructing weak signal image in the process of data processing. The theoretical and experimental results show that the PCA algorithm is more effective than the current multiline average algorithm in reducing noise, analyzing weak signal images and correcting the small rotation angle of CCD camera, and eliminating the system error caused by it.
【作者單位】： 中國科學(xué)院上海應(yīng)用物理研究所;中國科學(xué)院大學(xué);
【基金】：國家自然科學(xué)基金項目(11375255;11075198)
【分類號】：TP391.41

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本文編號：2364991