Browsing by Subject "Hyperspectral"
Now showing items 1-5 of 5
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Dual-Window Superpixel Data Augmentation for Hyperspectral Image Classification
(MDPI, 2020)Deep learning (DL) has been shown to obtain superior results for classification tasks in the field of remote sensing hyperspectral imaging. Superpixel-based techniques can be applied to DL, significantly decreasing training ... -
Extended Anisotropic Diffusion Profiles in GPU for Hyperspectral Imagery
(IEEE, 2019)Morphological profiles are a common approach for extracting spatial information from remote sensing hyperspectral images by extracting structural features. Other profiles can be built based on different approaches such as, ... -
On the relationship between optical variability, visual saliency, and eye fixations: a computational approach
(Association for Research in Vision and Ophthalmology, 2012)A hierarchical definition of optical variability is proposed that links physical magnitudes to visual saliency and yields a more reductionist interpretation than previous approaches. This definition is shown to be grounded ... -
TCANet for Domain Adaptation of Hyperspectral Images
(MDPI, 2019)The use of Convolutional Neural Networks (CNNs) to solve Domain Adaptation (DA) image classification problems in the context of remote sensing has proven to provide good results but at high computational cost. To avoid ... -
Texture Extraction Techniques for the Classification of Vegetation Species in Hyperspectral Imagery: Bag of Words Approach Based on Superpixels
(MDPI, 2020)Texture information allows characterizing the regions of interest in a scene. It refers to the spatial organization of the fundamental microstructures in natural images. Texture extraction has been a challenging problem ...