Effective anomaly space for hyperspectral anomaly detection

CI Chang - IEEE Transactions on Geoscience and Remote …, 2022 - ieeexplore.ieee.org
Due to unavailability of prior knowledge about anomalies, background suppression (BS) is a
crucial factor in anomaly detection (AD) evaluation. The difficulty in dealing with BS arises …

Co-seismic landslide mapping using Sentinel-2 10-m fused NIR narrow, red-edge, and SWIR bands

P Lu, W Shi, Q Wang, Z Li, Y Qin, X Fan - Landslides, 2021 - Springer
An accurate and timely inventory for major landslides triggered by seismic events is
essential for hazard assessment and risk governance. Sentinel-2 MultiSpectral Instrument …

[HTML][HTML] Spectral–spatial urban target detection for hyperspectral remote sensing data using artificial neural network

S Gakhar, KC Tiwari - The Egyptian Journal of Remote Sensing and Space …, 2021 - Elsevier
Hyperspectral remote sensing is opening new gateways for a multitude of applications with
an added advantage of high spectral and spatial resolution. Target detection of urban …

[PDF][PDF] Detection and Identification of Camouflaged Targets using Hyperspectral and LiDAR data.

D Yadav, MK Arora, KC Tiwari… - Defence Science …, 2018 - pdfs.semanticscholar.org
Camouflaging is the process of merging the target with the background with the aim to
reduce/delay its detection. It can be done using different materials/methods such as …

Detection of engineered surfaces using deep learning approach in AVIRIS-NG hyperspectral data

S Gakhar, KC Tiwari - Geocarto International, 2022 - Taylor & Francis
Hyperspectral remote sensing is opening new avenues for multitude of urban applications.
This paper extends target detection method for extraction of engineered surfaces or urban …

Selection of the best hybrid spectral similarity measure for characterising marine oil spills from multi-platform hyperspectral datasets

Deepthi, D Sankar, T Thomas - International Journal of …, 2023 - inderscienceonline.com
Marine oil pollution causes major economic crises in major industrial sectors like fishing,
shipping and tourism. It affects marine life and human even decades after spillage …

[HTML][HTML] Identification of most useful spectral ranges in improvement of target detection using hyperspectral data

D Yadav, MK Arora, KC Tiwari, JK Ghosh - The Egyptian Journal of Remote …, 2019 - Elsevier
Hyperspectral imaging, because of its high spectral content, has been used in many
surveillance and intelligence applications. Major issues in exploitation of HSI data, however …

Band selection for plastic classification using NIR hyperspectral image

H Kim, S Kim - 2016 16th International Conference on Control …, 2016 - ieeexplore.ieee.org
Recently, there are many plastics classification methods, because the importance of
recycling increases. In case of plastic, optical methods such as Near infrared (NIR) …

Comparative Assessment of Target-Detection Algorithms for Urban Targets Using Hyperspectral Data

S Gakhar, KC Tiwari - Photogrammetric Engineering & Remote …, 2021 - ingentaconnect.com
Hyperspectral data present better opportunities to exploit the treasure of spectral and spatial
content that lies within their spectral bands. Hyperspectral data are increasingly being …

Classification of Remotely Sensed Data Using Fisher's Linear Discriminant

BR Shivakumar, GP Raghudathesh - International Conference on VLSI …, 2023 - Springer
In place of time-consuming and expensive data collecting on the ground, remote sensing
allows for rapid, repeated coverage of enormous areas, with widespread practical …