Results 51 to 60 of about 30,598 (209)
Enhancing hyperspectral image unmixing with spatial correlations [PDF]
, 2010 This paper describes a new algorithm for hyperspectral image unmixing. Most unmixing algorithms proposed in the literature do not take into account the possible spatial correlations between the pixels.
Jean-Yves Tourneret +5 more
core +1 more source
Remote Sensing, 2022 For many urban studies it is necessary to obtain remote sensing images with high hyperspectral and spatial resolution by fusing the hyperspectral and panchromatic remote sensing images.
Rui Zhao, Shihong Du
doaj +1 more source
Correlation Hyperspectral Imaging
Physical Review LettersHyperspectral imaging aims at providing information on both the spatial and the spectral distribution of light, with high resolution. However, state-of-the-art protocols are characterized by an intrinsic trade-off imposing to sacrifice either resolution or image acquisition speed.
Gianlorenzo Massaro +2 more
openaire +4 more sources
SoftwareXIn recent years, publications have relied on either commercial software or custom-developed codes for the analysis of hyperspectral images. This practice has inadvertently restricted the broader adoption of hyperspectral imaging.
Billy G. Ram, Sunil GC, Xin Sun
doaj +1 more source
Supervised nonlinear spectral unmixing using a post-nonlinear mixing model for hyperspectral imagery [PDF]
, 2011 This paper presents a nonlinear mixing model for hyperspectral image unmixing. The proposed model assumes that the pixel reflectances are nonlinear functions of pure spectral components contaminated by an additive white Gaussian noise.
Altmann, Yoann +9 more
core +1 more source
Overlap-based feature weighting: The feature extraction of Hyperspectral remote sensing imagery [PDF]
Journal of Artificial Intelligence and Data Mining, 2015 Hyperspectral sensors provide a large number of spectral bands. This massive and complex data structure of hyperspectral images presents a challenge to traditional data processing techniques. Therefore, reducing the dimensionality of hyperspectral images
M. Imani, H. Ghassemian
doaj +1 more source
The Influence of Image Degradation on Hyperspectral Image Classification
Remote Sensing, 2022 Recent advances in hyperspectral remote sensing techniques, especially in the hyperspectral image classification techniques, have provided efficient support for recognizing and analyzing ground objects.
Congyu Li +3 more
doaj +1 more source
Hyperspectral image unmixing using a multiresolution sticky HDP [PDF]
, 2012 This paper is concerned with joint Bayesian endmember extraction and linear unmixing of hyperspectral images using a spatial prior on the abundance vectors.We propose a generative model for hyperspectral images in which the abundances are sampled from a ...
Hero, Alfred O. +3 more
core +1 more source
Quality criteria benchmark for hyperspectral imagery [PDF]
, 2005 Hyperspectral data appear to be of a growing interest over the past few years. However, applications for hyperspectral data are still in their infancy as handling the significant size of the data presents a challenge for the user community.
Christophe, Emmanuel +2 more
core +1 more source
Hyperspectral Image Change Detection Method Based on the Balanced Metric
SensorsChange detection, as a popular research direction for dynamic monitoring of land cover change, usually uses hyperspectral remote-sensing images as data sources. Hyperspectral images have rich spatial–spectral information, but traditional change detection
Xintao Liang +4 more
doaj +1 more source