Local structure tensor for multidimensional signal processing. Applications to medical image analysis

Abstract

Feature extraction and, particularly, orientation estimation of multidimensional images is of paramount importance for the Image Processing and Computer Vision communities. This dissertation focuses on this topic; specifically, we deal with the problem of local structure tensor (LST) estimation, as a mean of characterizing the local behavior of a multidimensional signal. The LST can be seen as a measure of the uncertainty of a multidimensional signal with respect to a given orientation. LST estimation can be achieved by estimating the local energy of a signal in different orientations. Then, the LST is computed as a linear combination of the local energy for each orientation with a tensor basis whose elements are calculated for each orientation. This kind of methods for the estimation of the LST is based on quadrature filters to obtain the local energy of the signal.