Application of fractal and wavelet analysis to Cerenkov images measured at the Whipple telescope

Multifractal and wavelet methods are mathematical tools used in pattern recognition and image parameterisation. Their application to images of Cerenkov light from air showers as obtained in the high-resolution camera of the Whipple telescope promises improved gamma/hadron separation over the whole energy range of interest. Using recent data of on/off-source measurements for the Crab nebula and Mrk421 the performance of fractal and wavelet parameters are tested and compared with that of the conventional Hillas parameterisation. The new parameters are independent of the image orientation and depend only on the shape, i.e. on the density distribution, of the image. Hence the methods are of special interest for the search of faint, extended, or diffuse sources of TeV gamma emission. The benefit of fractal and wavelet analyses to Cherenkov image analysis is discussed for the Whipple telescope as well as for an array of telescopes like VERITAS.