Abstract

We propose the use of the wavelet transform to characterize the time evolution of dynamic speckle patterns. We describe it by using as an example a method used for the assessment of the drying of paint. Optimal texture features are determined and the time evolution is described in terms of the Mahalanobis distance to the final (dry) state. From the behavior of this distance function, two parameters are defined that characterize the evolution. Because detailed knowledge of the involved dynamics is not required, the methodology could be implemented for other complex or poorly understood dynamic phenomena.

© 2002 Optical Society of America

Multiscale analysis of the intensity fluctuation in a time series of dynamic speckle patterns

Alejandro Federico and Guillermo H. Kaufmann
Appl. Opt. 46(11) 1979-1985 (2007)

Speckle activity images based on the spatial variance of the phase

Héctor Rabal, Nelly Cap, Marcelo Trivi, Ricardo Arizaga, Alejandro Federico, Gustavo E. Galizzi, and Guillermo H. Kaufmann
Appl. Opt. 45(34) 8733-8738 (2006)

Wavelet analysis of speckle patterns with a temporal carrier

Yu Fu, Cho Jui Tay, Chenggen Quan, and Hong Miao
Appl. Opt. 44(6) 959-965 (2005)

Sensitivity evaluation of dynamic speckle activity measurements using clustering methods

Pablo Etchepareborda, Alejandro Federico, and Guillermo H. Kaufmann
Appl. Opt. 49(19) 3753-3761 (2010)

Retrieving controlled motion parameters using two speckle pattern analysis techniques: spatiotemporal correlation and the temporal history speckle pattern

Rana Nassif, Christelle Abou Nader, Fabrice Pellen, Guy Le Brun, Marie Abboud, and Bernard Le Jeune
Appl. Opt. 52(31) 7564-7569 (2013)