We demonstrate the validity of wavelet-based processing for recognition and classification of three-dimensional phase
objects. One Fresnel digital hologram of each of the three-dimensional (3-D)
phase objects to be classified is recorded. The electronic holograms are processed digitally to permit
3-D object information to be retrieved as two-dimensional digital complex images. We use a Mexican-hat wavelet-
matched filter (WMF) to enhance the correlation peak and discriminate between the objects. The
WMF performs a wavelet transform (WT) to enhance the significant features of the images and the
correlation of the WT coefficients thus obtained. We compare the feasibility of a WMF-based
object classifier with the matched-filter-based classifier to classify our four 3-D
phase objects in a 3-D scene into true or false classes with minimal error.
© 2006 Optical Society of America
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