Results 51 to 60 of about 56,702 (212)

Nonlinear unmixing of hyperspectral images: Models and algorithms [PDF]

, 2013
When considering the problem of unmixing hyperspectral images, most of the literature in the geoscience and image processing areas relies on the widely used linear mixing model (LMM).
Bermudez, José Carlos Moreira, Dobigeon, Nicolas, Hero, Alfred O., McLaughlin, Steve, Richard, Cédric, Tourneret, Jean-Yves   +5 more
core   +8 more sources

Physically Based Predictive Modelling of Archaeological Proxies Using Cropmarks

Archaeological Prospection, EarlyView.
ABSTRACT Cropmarks, as archaeological proxies, offer a valuable means of detecting buried sites through remote sensing. Yet, the scalability of such methods across varied archaeological contexts remains underexplored, and AI‐based modelling approaches are still in early stages.
Elias Gravanis, Athos Agapiou
wiley   +1 more source

Editorial for Special Issue “Hyperspectral Imaging and Applications”

Remote Sensing, 2019
Due to advent of sensor technology, hyperspectral imaging has become an emerging technology in remote sensing. Many problems, which cannot be resolved by multispectral imaging, can now be solved by hyperspectral imaging.
Chein-I Chang, Meiping Song, Junping Zhang, Chao-Cheng Wu   +3 more
doaj   +1 more source

Remote Sensing Performance Enhancement in Hyperspectral Images [PDF]

Sensors, 2018
Hyperspectral images with hundreds of spectral bands have been proven to yield high performance in material classification. However, despite intensive advancement in hardware, the spatial resolution is still somewhat low, as compared to that of color and multispectral (MS) imagers. In this paper, we aim at presenting some ideas that may further enhance
openaire   +3 more sources

Advances in Hyperspectral Image Classification: Earth monitoring with statistical learning methods [PDF]

, 2013
Hyperspectral images show similar statistical properties to natural grayscale or color photographic images. However, the classification of hyperspectral images is more challenging because of the very high dimensionality of the pixels and the small number
Benediktsson, Jón Atli, Bruzzone, Lorenzo, Camps-Valls, Gustavo, Tuia, Devis   +3 more
core   +1 more source

Archaeological Damage Assessment in Conflict Zones: Integrating Satellite Imagery and Ground Surveys in Daraa, Syria

Archaeological Prospection, EarlyView.
ABSTRACT Satellite remote sensing is among the most significant modern methodologies supporting field archaeology. In addition to its efficiency in identifying archaeological sites, remote sensing offers a safe and cost‐effective approach in conflict zones.
Amal Al Kassem, Kristen Hopper, Ismael M. Ibraheem, Andreas Maier, Mohammad Khair Nassrallah, Jürgen Richter   +5 more
wiley   +1 more source

Cutting Through the Green: A Case for Grassland Archaeology Using UAV Multispectral Data

Archaeological Prospection, EarlyView.
ABSTRACT Advances in low‐altitude remote sensing are needed to improve the effectiveness of archaeological prospection in the Netherlands. The geomorphological situation and land use history make applying various remote sensing and geophysical technologies particularly challenging.
Roeland Emaus
wiley   +1 more source

Global Information and Structure Tensor Guided Collaborative Representation for Anomaly Detection

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Anomaly detection is susceptible to complex background and interference noise. Local anomaly detection and collaborative representation detection can effectively suppress background.
Meiping Song, Zhenyu Guo, Lan Li, Shihui Liu, Haimo Bao, Jiakang Li   +5 more
doaj   +1 more source

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 ...
Aiazzi B., Atkinson P.M., Breiman L., Caldelli R., Caldelli R., Cristophe E., David Megías, Fridrich J., Gersho A., Ho A.T.S., Jordi Serra-Ruiz, Lin E., Mielikainen J., Minguillón J., Minguillón J., Minguillón J., Motta G., Qin Q., Raudys S.J., Rey C., Sal D., Tamhankar H., Wang X., Wong F.C., Yeung M.   +24 more
core   +1 more source

Deep Learning Integration in Optical Microscopy: Advancements and Applications

Microscopy Research and Technique, EarlyView.
It explores the integration of DL into optical microscopy, focusing on key applications including image classification, segmentation, and computational reconstruction. ABSTRACT Optical microscopy is a cornerstone imaging technique in biomedical research, enabling visualization of subcellular structures beyond the resolution limit of the human eye ...
Pottumarthy Venkata Lahari, Sagnika Dutta, H. Deeksha, Samreen A. Patel, Budheswar Dehury, Nirmal Mazumder   +5 more
wiley   +1 more source