The notion of a multiresolution support is introduced. This is a sequence of boolean images, related to signi cant pixels at each of a number of resolution levels. The multiresolution support is then used for noise suppression, in the context of image ltering, or iterative image restoration. Algorithmic details, and a range of practical examples, illustrate this approach.

We propose a new subdivision scheme derived from the Lounsbery’s regular 1:4 face split, allowing multiresolution analysis of irregularly subdivided triangular meshes by the wavelet transforms. Some experimental results on real medical meshes prove the efficiency of this approach in multiresolution schemes. In addition we show the effectiveness of the proposed algorithm for lossless compression.

A new nonlinear representation of multiresolution decompositions and new thresholding adapted to the presence of discontinuities are presented and analyzed. They are based on a nonlinear modification of the multiresolution details coming from an initial (linear or nonlinear) scheme and on a data dependent thresholding. Stability results are derived. Numerical advantages are demonstrated on vari...

Abstract: A wavelet basis is an orthonormal basis for L(R), the space of square-integrable functions on the real line, of the form {gnk}n,k∈Z, where gnk(t) = 2 n/2 g(2t − k) and g is a single fixed function, the wavelet. Each multiresolution analysis for L(R) determines such a basis. To find a multiresolution analysis, one can begin with a dilation equation f(t) = ∑ ck f(2t− k). If the solution...

We implemented a 3D co-registration technique based on mutual information (MI) including 2D image matching as a coarse pre-registration. The 2D coarse pre-registration was performed in the transverse, sagittal and coronal planes sequentially, and all six parameters were then optimized as fine registration. Normalized mutual information (NMI) was also examined as another entropy-based measure th...