奇异值分解
计算机科学
数字全息显微术
虚假关系
全息术
人工智能
光学
相(物质)
计算机视觉
数字全息术
降维
还原(数学)
算法
物理
数学
机器学习
几何学
量子力学
作者
Harshal Chaudhari,Rishikesh Kulkarni,Pradeep Kumar Sundaravadivelu,Rajkumar P. Thummer,M. K. Bhuyan
标识
DOI:10.1016/j.optlaseng.2023.107853
摘要
A dimensionality reduction technique based on singular value decomposition (SVD) is proposed for the aberration and spurious fringe removal from the phase measurement in off-axis digital holographic microscopy. The SVD of complex-valued virtual image obtained from numerically reconstructed hologram is computed. The phase aberration and spurious fringe compensated phase estimate is obtained by appropriate selection of singular values to reconstruct the denoised phase image. In order to remove the artifacts created along the x and y axis due to the SVD, the filtering procedure is implemented by rotating the phase image a fixed number of times. The effective denoised image is obtained by the weighted combination of denoised image evaluated for each rotation. Simulation and experimental studies are conducted to demonstrate the practical applicability of the proposed method.
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