Now showing items 1-10 of 10
Estrategias de sostenibilidad y responsabilidad social en las universidades españolas: una herramienta para su evaluación
(Universidad de Granada. Facultad de Ciencias de la Educación, 2012)
TCANet for Domain Adaptation of Hyperspectral Images
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 ...
Multiresolution rendering based on GPGPU computing
(Research Institute of Intelligent Computer Systems, 2013)
The problem of visualizing large volumetric datasets is appealing for computation on the GPU. Nevertheless, the design of GPU volume rendering solutions must deal with the limited available memory in a graphics card. In ...
Alignment of Hyperspectral Images Using KAZE Features
Image registration is a common operation in any type of image processing, specially in remote sensing images. Since the publication of the scale–invariant feature transform (SIFT) method, several algorithms based on feature ...
HypeRvieW: an open source desktop application for hyperspectral remote-sensing data processing
(Taylor & Francis, 2016)
In this article, we present a desktop application for the analysis, reference data generation, registration, and supervised spatial-spectral classification of hyperspectral remote-sensing images through a simple and intuitive ...
A multi-device version of the HYFMGPU algorithm for hyperspectral scenes registration
Hyperspectral image registration is a relevant task for real-time applications like environmental disasters management or search and rescue scenarios. Traditional algorithms were not really devoted to real-time performance, ...
Fourier–Mellin registration of two hyperspectral images
(Taylor & Francis, 2017-03-21)
Hyperspectral images contain a great amount of information which can be used to more robustly register such images. In this article, we present a phase correlation method to register two hyperspectral images that takes ...
GPU Accelerated FFT-Based Registration of Hyperspectral Scenes
Registration is a fundamental previous task in many applications of hyperspectrometry. Most of the algorithms developed are designed to work with RGB images and ignore the execution time. This paper presents a phase ...
Texture Extraction Techniques for the Classification of Vegetation Species in Hyperspectral Imagery: Bag of Words Approach Based on Superpixels
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 ...
Dual-Window Superpixel Data Augmentation for Hyperspectral Image Classification
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 ...