TABLE OF CONTENTS In the previous chapters, we have thoroughly discussed the 2-D CWT and some of its applications. Then we have made the connection with the group theoretical origins of the method, thus establishing a general framework, based on the coherent state formalism. In the present chapter, we will apply the same technique to a number of different situations involving higher dimensions: wavelets in 3-D space 
3, wavelets in n ( n > 3), and wavelets on the 2-sphere S 2. Then, in the next chapter, we will treat time-dependent wavelets, that is, wavelets on space time, designed for motion analysis.
In all cases, the technique is the same. First one identifies the manifold on which the signals are defined and the appropriate group of transformations acting on the latter. Next one chooses a square integrable representation of that group, possibly modulo some subgroup. Then one constructs wavelets as admissible vectors and derives the corresponding wavelet transform.
Some physical phenomena are intrinsically multiscale and three-dimensional. Typical examples may be found in fluid dynamics, for instance the appearance of coherent structures in turbulent flows, or the disentangling of a wave train in (mostly underwater) acoustics, as discussed above. In such cases, a 3-D wavelet analysis is clearly more adequate and likely to yield a deeper understanding [56]. The same is true for many problems in astrophysics, such as galaxy/void counting or grouping, or cluster structure analysis. Hence we will also describe briefly the 3-D CWT, following the general...
