基于UKF的数字全息图像多分量相位估计

2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG) Pub Date : 2013-12-01 DOI:10.1109/NCVPRIPG.2013.6776212

Rahul G. Waghmare, Deepak Mishra, K. SaiSubrahmanyamG.R.

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引用次数: 1

摘要

采用多光束从不同角度照射物体，记录多光束产生的干涉图样，可以同时测量物体的多维变形。该技术涉及到从重建干涉波场的一个记录中可靠地估计产生的多个相位图。本文提出了一种基于无气味卡尔曼滤波(Unscented Kalman Filter, UKF)的新方法，用于估计数字全息图像中复杂多分量信号的多相位映射。该方法中使用的状态空间模型以相分量的泰勒级数展开为过程模型，以极坐标到笛卡尔坐标的转换为测量模型。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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UKF based multi-component phase estimation in digital holographic Moiré

Simultaneous measurement of multi-dimensional deformations can be done in digital holographic Moiré by illuminating the object with multiple beams from different angles and recording the interference pattern due to multiple beams. This technique involves reliable estimation of resultant multiple phase maps from a one record of the reconstructed interference moiré field. In this paper, we introduce a novel method, based on Unscented Kalman Filter (UKF), for the estimation of multiple phase maps from a complex multi-component signal encountered in digital holographic moiré. The State space model used in this method is determined by Taylor series expansion of phase component as process model and polar to Cartesian conversion as measurement model.

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2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)

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