16 citations · 27 across the 6 of their papers we have counts for
6 papers
Randomized RX for target detection
Fatih Nar, Adrián Pérez-Suay, José Antonio Padrón +1
This work tackles the target detection problem through the well-known global RX method. The RX method models the clutter as a multivariate Gaussian distribution, and has been exten…
Nonlinear Cook distance for Anomalous Change Detection
José A. Padrón Hidalgo, Adrián Pérez-Suay, Fatih Nar +1
In this work we propose a method to find anomalous changes in remote sensing images based on the chronochrome approach. A regressor between images is used to discover the most {\em…
Sparsity-driven Digital Terrain Model Extraction
Fatih Nar, Erdal Yilmaz, Gustau Camps-Valls
We here introduce an automatic Digital Terrain Model (DTM) extraction method. The proposed sparsity-driven DTM extractor (SD-DTM) takes a high-resolution Digital Surface Model (DSM…
Efficient Nonlinear RX Anomaly Detectors
José A. Padrón Hidalgo, Adrián Pérez-Suay, Fatih Nar +1
Current anomaly detection algorithms are typically challenged by either accuracy or efficiency. More accurate nonlinear detectors are typically slow and not scalable. In this lette…
SAR Image Despeckling Using Quadratic-Linear Approximated L1-Norm
Fatih Nar
Speckle noise, inherent in synthetic aperture radar (SAR) images, degrades the performance of the various SAR image analysis tasks. Thus, speckle noise reduction is a critical prep…
Sparsity-driven weighted ensemble classifier
Atilla Ozgur, Hamit Erdem, Fatih Nar
In this study, a novel sparsity-driven weighted ensemble classifier (SDWEC) that improves classification accuracy and minimizes the number of classifiers is proposed. Using pre-tra…