Artículos de revistas
Probability mapping images in dynamic speckle classification
Fecha
2013-02Registro en:
Passoni, Isabel; Rabal, Hector Jorge; Meschino, Gustavo; Trivi, Marcelo; Probability mapping images in dynamic speckle classification; Optical Society of America; Applied Optics; 52; 4; 2-2013; 726-733
1559-128X
Autor
Passoni, Isabel
Rabal, Hector Jorge
Meschino, Gustavo
Trivi, Marcelo
Resumen
We propose the use of a learning procedure to identify regions of similar dynamics in speckle image sequences that includes more than one descriptor. This procedure is based on the application of a naïve Bayes statistical classifier comprising the use of several descriptors. The class frontiers can be depicted so that the proportion of identified regions may be measured. To demonstrate the results, assembly of an RGB image, where each plane (R, G, and B) is associated with a particular region (class), was labeled according to its biospeckle dynamics. A high brightness in one color means a high probability of the pixel belonging to the corresponding class, and vice versa.