Characterization of spatial–temporal patterns in dynamic speckle sequences using principal component analysis

Abstract

Abstract. Speckle is being used as a characterization tool for the analysis of the dynamics of slow-varying phenomena occurring in biological and industrial samples at the surface or near-surface regions. The retrieved data take the form of a sequence of speckle images. These images contain information about the inner dynamics of the biological or physical process taking place in the sample. Principal component analysis (PCA) is able to split the original data set into a collection of classes. These classes are related to processes showing different dynamics. In addition, statistical descriptors of speckle images are used to retrieve information on the characteristics of the sample. These statistical descriptors can be calculated in almost real time and provide a fast monitoring of the sample. On the other hand, PCA requires a longer computation time, but the results contain more information related to spatial-temporal patterns associated to the process under analysis. This contribution merges both descriptions and uses PCA as a preprocessing tool to obtain a collection of filtered images, where statistical descriptors are evaluated on each of them. The method applies to slow-varying biological and industrial processes.

Quantitative Laser Biospeckle Method for the Evaluation of the Activity of Trypanosoma cruzi Using VDRL Plates and Digital Analysis

“…The methodology is based on laser dynamic speckle interferometry, called Biospeckle interferometry [7][8]. Different Biospeckle descriptors have been proposed and evaluated from the performance point of view [9] and others have explored the combination of spatial—temporal patterns for the analysis of the dynamics of slow-varying phenomena [10]. In the present work the Biospeckle technique is applied to several samples, following the time evolution of the activity of the Biospeckle patterns.…”

Visualization of in vitro deep blood vessels using principal component analysis based laser speckle imaging

“…However, in these invasive methods a pulsed laser or external agents are needed to modify the contrast to improve the visualization of blood vessels. In Refs [9,10] the authors use a noninvasive image processing method based on PCA to analyze the dynamic speckle patterns in maize seed, on apple and the drying process of a painted coin. In these works, PCA is used as a filtering process to study spatially and temporally the dynamic of the speckle patterns.…”