Hyperspectral imaging involves large amounts of information. This paper presents a
technique for dimensionality reduction to deal with hyperspectral images. The proposed …

Effective fault diagnosis can be obtained by using multiblock global orthogonal projections
to latent structures (MBGOPLS), but there exist certain limitations in this method in terms of …

This work presents the application of a novel technique on dimensionality reduction to deal
with multispectral images. A distance based on mutual information is used to construct a …

Feature selection and dimensionality reduction are crucial research fields in pattern
recognition. This work presents the application of a novel technique on dimensionality …

This work tackles the segmentation of apparent-motion from a bottom-up perspective. When
no information is available to build prior high-level models, the only alternative are bottom …

This chapter deals with the problem of segmentation of apparent-motion. Apparent-motion
segmentation can be stated as the identification and classification of regions undergoing the …

There is no doubt about how useful and valuable the information provided by the
hyperspectral sensors can be. Image segmentation procedures can take advantage of this …

The title of the thesis focuses the attention on hyperspectral image segmentation, that is, we
want to detect salient regions in a hyperspectral image and isolate them as accurate as …