A Novel Method for LWIR Hyperspectral Target Detection by Means of a Subspace-Based Approach
نویسندگان
چکیده
منابع مشابه
A New Dictionary Construction Method in Sparse Representation Techniques for Target Detection in Hyperspectral Imagery
Hyperspectral data in Remote Sensing which have been gathered with efficient spectral resolution (about 10 nanometer) contain a plethora of spectral bands (roughly 200 bands). Since precious information about the spectral features of target materials can be extracted from these data, they have been used exclusively in hyperspectral target detection. One of the problem associated with the detect...
متن کاملA Novel Noise Reduction Method Based on Subspace Division
This article presents a new subspace-based technique for reducing the noise of signals in time-series. In the proposed approach, the signal is initially represented as a data matrix. Then using Singular Value Decomposition (SVD), noisy data matrix is divided into signal subspace and noise subspace. In this subspace division, each derivative of the singular values with respect to rank order is u...
متن کاملA Novel Noise Reduction Method Based on Subspace Division
This article presents a new subspace-based technique for reducing the noise of signals in time-series. In the proposed approach, the signal is initially represented as a data matrix. Then using Singular Value Decomposition (SVD), noisy data matrix is divided into signal subspace and noise subspace. In this subspace division, each derivative of the singular values with respect to rank order is u...
متن کاملAdaptive Subspace Target Detection in Hyperspectral Imagery
* Corresponding author. Abstract –Adaptive subspace detectors are widely used for low probability and anomaly detection. The complex remote sensing conditions in which hyperspectral imagery is obtained make the detector performance evaluation a non-trivial task. Many of the detector design parameters can only be studied empirically for their effects on detection performance. In this paper, hype...
متن کاملA New Subspace Method for Anomaly Detection in Hyperspectral Imagery
Recently, anomaly detection has been one of the most interesting researches in hyperspectral images (HSIs) applications. Generally, anomalies in HSIs are rare pixels. The Reed–Xiaoli (RX) algorithm is a benchmark anomaly detector for HSIs, which uses the local Gaussian model generally [1]. But for RX algorithm there are two issues to be considered. First it requires the estimation of model para...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Proceedings
سال: 2019
ISSN: 2504-3900
DOI: 10.3390/proceedings2019027047