Collecting airborne and spaceborne intelligence, surveillance, and reconnaissance (ISR)
information is mandatory for addressing the defense challenges posed in the 21st century. A …

Hyperspectral imagery can obtain hundreds of narrow spectral bands of ground objects. The
abundant and detailed spectral information offers a unique diagnostic identification ability for …

Obtaining models that capture imaging markers relevant for disease progression and
treatment monitoring is challenging. Models are typically based on large amounts of data …

Anomaly localization is an important problem in computer vision which involves localizing
anomalous regions within images with applications in industrial inspection, surveillance …

Anomaly detection has become an important remote sensing application due to the
abundant spectral and spatial information contained in hyperspectral images. Recently …

In this paper, we propose a hyperspectral image anomaly detection model by the use of
background joint sparse representation (BJSR). With a practical binary hypothesis test …

Hyperspectral sensors are passive instruments that record reflected electromagnetic
radiation in tens or hundreds of narrow and consecutive spectral bands. In the last two …

In this article, a novel hyperspectral anomaly detection method with kernel Isolation Forest
(iForest) is proposed. The method is based on an assumption that anomalies rather than …

Hyperspectral anomaly detection methods based on representation model have attracted
much attention in recent years. In the method, a background dictionary is used to represent …

Hyperspectral anomaly detection (AD) is an important problem in remote sensing field. It can
make full use of the spectral differences to discover certain potential interesting regions …