Hard-thresholding-based algorithms have seen various advantages for sparse optimization in controlling the sparsity and allowing fast computation. Recent research shows that when techniques of Newton-type methods are integrated, their numerical performance can be improved surprisingly. This paper develops a gradient projection Newton pursuit algorithm mainly adopts hard-thresholding operator em...

In order to summarize and represent graphically multidimensional data in statistics, projection pursuit methods look for projection axes which reveal structures, such as possible groups or outliers, by optimizing a function called projection index. To determine these possible interesting structures, it is necessary to choose an optimization method capable to find not only the global optimum of ...

Hyperspectral images contain rich and fine spectral information, an improvement of land use/cover classification accuracy is expected from the use of such images. However, the classification methods that have been successfully applied to multispectral data in the past are not as effective as to hyperspectral data. The major cause is that the size of training data set does not correspond to the ...

Hyperspectral images have a higher spectral resolution (i.e., a larger number of bands covering the electromagnetic spectrum), but a lower spatial resolution with respect to multispectral or panchromatic acquisitions. For increasing the capabilities of the data in terms of utilization and interpretation, hyperspectral images having both high spectral and spatial resolution are desired. This can...

Hyperspectral imaging, even when restricted to the visible spectrum range, allows what is indiscriminable to the human visual system to become discriminable. The typical human visual system (HVS) projects the light spectrum, the determinant of color, into a threedimensional subspace. The basis is determined by the spectral response of the three types of cones. The response has been modeled as t...

The problem of segmenting multidimensional images, in particular hyperspectral images, is still an open subject. The main issue is related to preserving the multidimensional character of the signals throughout the segmentation process avoiding an early projection onto a 2D plane with the consequent loss of the wealth of information these images provide. The approach followed here is based on th...