Patterns with a local roll structure arise in many diverse physical sy
stems which have little in common at the microscopic level. In this pa
per we construct an algorithm based on the wavelet transform that can
be used as a diagnostic tool to extract from such patterns macroscopic
information like the local director field, the local amplitude away f
rom defects, and slowly varying fields, such as mean drift, which may
be soft modes of pattern, It allows a precise detection of phase grain
boundaries and point defects. Several tests are conducted on numerica
lly generated signals to demonstrate the applicability and precision o
f the algorithm. Finally, the algorithm is applied to actual experimen
tal convection patterns, allowing us to draw several conclusions about
the nature of the wave director field in such patterns. (C) 1998 Publ
ished by Elsevier Science B.V.