A wavelet packets equalization technique to reveal the multiple spatial-scale nature of coronal structures

Precise determination of onset times of dynamical events as observed by coronagraphs requires a high-degree-of-accuracy tracking of the structures involved. In particular, early steps in the evolution turn to be of utmost importance. However, corresponding features often lack the sharpness needed to obtain unambiguous results. To overcome this constraint, we developed a multiresolution image processing technique applicable to any coronagraph data set to enhance both boundaries and internal details of originally faint and diffuse structures. The method implemented employs a multi-level decomposition scheme (splitting algorithm of a wavelet packet on non-orthogonal wavelets) via the a trous wavelet transform, local noise reduction and interactive weighted recomposition. This approach represents a major advance towards unambiguous image interpretation and provides a means for the quantification of stationary and dynamic coronal structures required for conducting morphological studies. A range of example applications based on LASCO-C1, -C2, and -C3 data sets are shown. Different reconstruction strategies are discussed.