Principal component analysis in the spectral analysis of the dynamic laser speckle patterns

K M Ribeiro,T Sáfadi,R A Braga Jr,D D Ferreira,G W Horgan

doi:10.2971/jeos.2014.14009

Abstract

Dynamic laser speckle is a phenomenon that interprets an optical patterns formed by illuminating a surface under changes with coherent light. Therefore, the dynamic change of the speckle patterns caused by biological material is known as biospeckle. Usually, these patterns of optical interference evolving in time are analyzed by graphical or numerical methods, and the analysis in frequency domain has also been an option, however involving large computational requirements which demands new approaches to filter the images in time. Principal component analysis (PCA) works with the statistical decorrelation of data and it can be used as a data filtering. In this context, the present work evaluated the PCA technique to filter in time the data from the biospeckle images aiming the reduction of time computer consuming and improving the robustness of the filtering. It was used 64 images of biospeckle in time observed in a maize seed. The images were arranged in a data matrix and statistically uncorrelated by PCA technique, and the reconstructed signals were analyzed using the routine graphical and numerical methods to analyze the biospeckle. Results showed the potential of the PCA tool in filtering the dynamic laser speckle data, with the definition of markers of principal components related to the biological phenomena and with the advantage of fast computational processing.

Highlights

Dynamic laser speckle, known as biospeckle when applied to biological materials, is an optical technique that processes the interference patterns formed when a material is illuminated by coherent light
4.3 Random selection of some principal components to application of the inverse Principal component analysis (PCA) transform. These results show that the preprocessing with PCA using the last h principal components served as a high pass filter, highlighting the high frequencies, such as in the embryonic portion, and filtering of the lowest frequencies, which are linked to the biological activity of the endosperm, as discussed by Cardoso et al [7]
Principal component analysis was proposed as tool to spectral analysis of dynamic laser speckle data and showed to be a powerful tool to analyze biospeckle data, allowing the implementation of filters with different frequency pass band ranges for data analysis concerning to the temporal Fourier transform

Summary

Introduction

Known as biospeckle when applied to biological materials, is an optical technique that processes the interference patterns formed when a material is illuminated by coherent light. It is a non-destructive technique and that has been validated as a tool for analysis and quantification of biological activity in the material under study [1]. Some examples of recent application of this tool are the works of Zakharov et al [4] imaging blood flow in rodent brain, Mavilio et al [5] studying the process of paint drying, Ansari and Nirala [6] monitoring the maturation of Indian fruits, among others. The high number of applications of biospeckle brings with themselves the need for techniques of image and signal processing that can help in the interpretation, and offer additional information derived from these optical interference patterns

Methods

Results

Conclusion