Visualizing Near Infrared Hyperspectral Images with Generative Adversarial Networks
Remote Sensing, 2020 The visualization of near infrared hyperspectral images is valuable for quick view and information survey, whereas methods using band selection or dimension reduction fail to produce good colors as reasonable as corresponding multispectral images.
Rongxin Tang, Hualin Liu, Jingbo Wei
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LAND COVER CHANGE DETECTION BASED ON GENETICALLY FEATURE AELECTION AND IMAGE ALGEBRA USING HYPERION HYPERSPECTRAL IMAGERY [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2015 The Earth has always been under the influence of population growth and human activities. This process causes the changes in land use. Thus, for optimal management of the use of resources, it is necessary to be aware of these changes.
S. T. Seydi, M. Hasanlou
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A General Deep Learning Point–Surface Fusion Framework for RGB Image Super-Resolution
Remote Sensing, 2023 Hyperspectral images are usually acquired in a scanning-based way, which can cause inconvenience in some situations. In these cases, RGB image spectral super-resolution technology emerges as an alternative.
Yan Zhang +3 more
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Bayesian estimation of linear mixtures using the normal compositional model. Application to hyperspectral imagery [PDF]
, 2010 This paper studies a new Bayesian unmixing algorithm for hyperspectral images. Each pixel of the image is modeled as a linear combination of so-called endmembers.
Eches, Olivier +3 more
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Multi-channel volume density neural radiance field for hyperspectral imaging
Scientific ReportsHyperspectral imaging and Neural Radiance Field (NeRF) can be combined in powerful ways. With limited hyperspectral images, NeRF can generate images of objects with spectral information from arbitrary viewpoints, which can effectively mitigate defects ...
Runchuan Ma, Sailing He
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Adaptive Markov random fields for joint unmixing and segmentation of hyperspectral image [PDF]
, 2013 Linear spectral unmixing is a challenging problem in hyperspectral imaging that consists of decomposing an observed pixel into a linear combination of pure spectra (or endmembers) with their corresponding proportions (or abundances). Endmember extraction
Eches, Olivier +3 more
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Hyperspectral imaging for cancer surgical margin delineation: registration of hyperspectral and histological images [PDF]
SPIE Proceedings, 2014 The determination of tumor margins during surgical resection remains a challenging task. A complete removal of malignant tissue and conservation of healthy tissue is important for the preservation of organ function, patient satisfaction, and quality of life.
Guolan Lu +4 more
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Illumination invariance and shadow compensation on hyperspectral images [PDF]
, 2014 To obtain intrinsic reflectance of the scene by hyperspectral imaging systems has been a scientific and engineering challenge. Factors such as illumination variations, atmospheric effects and viewing geometries are common artefacts which modulate the way
Ibrahim, Izzati
core
A novel semi-fragile forensic watermarking scheme for remote sensing images [PDF]
, 2011 Peer-reviewedA semi-fragile watermarking scheme for multiple band images is presented. We propose to embed a mark into remote sensing images applying a tree structured vector quantization approach to the pixel signatures, instead of processing each band ...
Serra Ruiz, Jordi +3 more
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Full-scale semantic segmentation of hyperspectral imaging based on spatial spatial-spectral joint network [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information SciencesHyperspectral images contain dozens or even hundreds of spectral bands, which contain rich spectral information and help distinguish different ground objects.
H. Wu, H. Wu, C. Li, Y. Li
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