RT Journal Article
T1 An Approach for the Customized High-Dimensional Segmentation of Remote Sensing Hyperspectral Images.
A1 Priego, Blanca
A1 Duro, Richard J
K1 Cellular automata
K1 Differential evolution
K1 Evolutionary algorithm
K1 Hyperspectral image classification
K1 Hyperspectral image segmentation
K1 Remote sensing
AB This paper addresses three problems in the field of hyperspectral image segmentation: the fact that the way an image must be segmented is related to what the user requires and the application; the lack and cost of appropriately labeled reference images; and, finally, the information loss problem that arises in many algorithms when high dimensional images are projected onto lower dimensional spaces before starting the segmentation process. To address these issues, the Multi-Gradient based Cellular Automaton (MGCA) structure is proposed to segment multidimensional images without projecting them to lower dimensional spaces. The MGCA structure is coupled with an evolutionary algorithm (ECAS-II) in order to produce the transition rule sets required by MGCA segmenters. These sets are customized to specific segmentation needs as a function of a set of low dimensional training images in which the user expresses his segmentation requirements. Constructing high dimensional image segmenters from low dimensional training sets alleviates the problem of lack of labeled training images. These can be generated online based on a parametrization of the desired segmentation extracted from a set of examples. The strategy has been tested in experiments carried out using synthetic and real hyperspectral images, and it has been compared to state-of-the-art segmentation approaches over benchmark images in the area of remote sensing hyperspectral imaging.
PB MDPI
YR 2019
FD 2019-06-29
LK http://hdl.handle.net/10668/14203
UL http://hdl.handle.net/10668/14203
LA en
NO Priego B, Duro RJ. An Approach for the Customized High-Dimensional Segmentation of Remote Sensing Hyperspectral Images. Sensors (Basel). 2019 Jun 29;19(13):2887
DS RISalud
RD Apr 12, 2025