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   Articles with "hyperspectral anomaly" as a keyword



Hyperspectral anomaly detection with semisupervised variational background inference and multi-scale masked convolutions

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recommendations! Published in 2025 at "International Journal of Remote Sensing"

DOI: 10.1080/01431161.2025.2459214

Abstract: ABSTRACT Hyperspectral anomaly detection plays a significant role in various applications and industries. However, most detection methods based on background reconstruction cannot accurately model the background distribution of hyperspectral images (HSIs). As a result, they… read more here.

Keywords: detection; hyperspectral anomaly; anomaly detection; multi scale ... See more keywords

Hyperspectral anomaly detection: a performance comparison of existing techniques

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recommendations! Published in 2022 at "International Journal of Digital Earth"

DOI: 10.1080/17538947.2022.2146770

Abstract: ABSTRACT Anomaly detection in Hyperspectral Imagery (HSI) has received considerable attention because of its potential application in several areas. Numerous anomaly detection algorithms for HSI have been proposed in the literature; however, due to the… read more here.

Keywords: performance comparison; detection; hyperspectral anomaly; anomaly detection ... See more keywords

Hyperspectral Anomaly Detection Based on Intrinsic Image Decomposition and Background Subtraction

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recommendations! Published in 2025 at "IEEE Access"

DOI: 10.1109/access.2025.3530437

Abstract: Hyperspectral anomaly detection is a detection of abnormal targets in a region based on spectral and spatial information under the premise of no prior knowledge of the target, which is a very important research topic… read more here.

Keywords: detection; image decomposition; hyperspectral anomaly; anomaly detection ... See more keywords

Hyperspectral Anomaly Detection by Fractional Fourier Entropy

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recommendations! Published in 2019 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"

DOI: 10.1109/jstars.2019.2940278

Abstract: Anomaly detection is an important task in hyperspectral remote sensing. Most widely used detectors, such as Reed–Xiaoli (RX), have been developed only using original spectral signatures, which may lack the capability of signal enhancement and… read more here.

Keywords: hyperspectral anomaly; anomaly detection; fourier entropy; fractional fourier ... See more keywords
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Background Purification Framework With Extended Morphological Attribute Profile for Hyperspectral Anomaly Detection

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recommendations! Published in 2021 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"

DOI: 10.1109/jstars.2021.3103858

Abstract: Hyperspectral anomaly detection has attracted extensive interests for its wide use in military and civilian fields, and three main categories of detection methods have been developed successively over past few decades, including statistical model-based, representation-based,… read more here.

Keywords: purification framework; detection; hyperspectral anomaly; background purification ... See more keywords

Self-Adaptive Low-Rank and Sparse Decomposition for Hyperspectral Anomaly Detection

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recommendations! Published in 2022 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"

DOI: 10.1109/jstars.2022.3172120

Abstract: Hyperspectral anomaly detection is a widely used technique for exploring target of interest in hyperspectral images (HSIs). In recent years, the low-rank and sparse-decomposition-based anomaly detection model has attracted extensive attention. However, these models suffer… read more here.

Keywords: hyperspectral anomaly; rank sparse; low rank; detection ... See more keywords

Normalizing Flow-Based Probability Distribution Representation Detector for Hyperspectral Anomaly Detection

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recommendations! Published in 2022 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"

DOI: 10.1109/jstars.2022.3182538

Abstract: Due to the powerful reconstruction ability, deep learning based hyperspectral anomaly detection methods have been prevalent in recent years. However, the capability of neural networks and the meaning of latent space remains unexplainable to some… read more here.

Keywords: normalizing flow; hyperspectral anomaly; detection; anomaly detection ... See more keywords

Subfeature Ensemble-Based Hyperspectral Anomaly Detection Algorithm

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recommendations! Published in 2022 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"

DOI: 10.1109/jstars.2022.3191725

Abstract: Hyperspectral images (HSIs) have always played an important role in remote sensing applications. Anomaly detection has become a hot spot in HSI processing in recent years. The popular detecting method is to accurately segment anomalies… read more here.

Keywords: hyperspectral anomaly; detection algorithm; subfeature; detection ... See more keywords

Learning-Free Hyperspectral Anomaly Detection With Unpredictive Frequency Residual Priors

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recommendations! Published in 2022 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"

DOI: 10.1109/jstars.2022.3194203

Abstract: Hyperspectral anomaly detection aims to fast and credibly find nontrivial candidate targets without prior knowledge, which has become an increasingly pressing need as imagery swath and resolution are growing rapidly. Relevant state-of-the-art learning-based anomaly detection… read more here.

Keywords: hyperspectral anomaly; frequency; learning free; detection ... See more keywords

Dynamic Negative Sampling Autoencoder for Hyperspectral Anomaly Detection

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recommendations! Published in 2022 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"

DOI: 10.1109/jstars.2022.3220514

Abstract: Hyperspectral anomaly detection (HAD) aims at detecting the anomalies without any prerequisite information, which gains lots of attention in recent years. Most of existing detectors locate the anomalies by eliminating the background. The background is… read more here.

Keywords: negative sampling; hyperspectral anomaly; dynamic negative; anomaly detection ... See more keywords

Logarithmic Kernel Relaxed Collaborative Representation With Scaled MST Dictionary Construction for Hyperspectral Anomaly Detection

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recommendations! Published in 2024 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"

DOI: 10.1109/jstars.2024.3476319

Abstract: Representation-based anomaly detection methods are one of the most popular methods in hyperspectral anomaly detection. Nevertheless, linear models of have difficulties in adequately describing complex data and generating a decision boundary for anomaly-background separation. To… read more here.

Keywords: detection; method; hyperspectral anomaly; representation ... See more keywords