Anomaly Detection from Hyperspectral Imagery using Transform-based Feature Selection and Local Spatial Auto-correlation Index
نویسندگان
چکیده
منابع مشابه
3D Gabor Based Hyperspectral Anomaly Detection
Hyperspectral anomaly detection is one of the main challenging topics in both military and civilian fields. The spectral information contained in a hyperspectral cube provides a high ability for anomaly detection. In addition, the costly spatial information of adjacent pixels such as texture can also improve the discrimination between anomalous targets and background. Most studies miss the wort...
متن کاملKernel-Based Anomaly Detection in Hyperspectral Imagery
In this paper we present a nonlinear version of the wellknown anomaly detection method referred to as the RXalgorithm. Extending this algorithm to a feature space associated with the original input space via a certain nonlinear mapping function can provide a nonlinear version of the RX-algorithm. This nonlinear RX-algorithm, referred to as the kernel RX-algorithm, is basically intractable mainl...
متن کاملAnomaly Detection from Hyperspectral Remote Sensing Imagery
Hyperspectral remote sensing imagery contains much more information in the spectral domain than does multispectral imagery. The consecutive and abundant spectral signals provide a great potential for classification and anomaly detection. In this study, two real hyperspectral data sets were used for anomaly detection. One data set was an Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) da...
متن کاملAnomaly detection and compensation for hyperspectral imagery
Hyperspectral sensors observe hundreds or thousands of narrow contiguous spectral bands. The use of hyperspectral imagery for remote sensing applications is new and promising, yet the characterization and analysis of such data by exploiting both spectral and spatial information have not been extensively investigated thus far. A generic methodology is presented for detecting and compensating ano...
متن کاملAnomaly detection and classification for hyperspectral imagery
Anomaly detection becomes increasingly important in hyperspectral image analysis, since hyperspectral imagers can now uncover many material substances which were previously unresolved by multispectral sensors. Two types of anomaly detection are of interest and considered in this paper. One was previously developed by Reed and Yu to detect targets whose signatures are distinct from their surroun...
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: Korean Journal of Remote Sensing
سال: 2012
ISSN: 1225-6161
DOI: 10.7780/kjrs.2012.28.4.2