no code implementations • 8 Dec 2020 • Fatih Nar, Adrián Pérez-Suay, José Antonio Padrón, Gustau Camps-Valls
This work tackles the target detection problem through the well-known global RX method.
no code implementations • 8 Dec 2020 • José A. Padrón Hidalgo, Adrián Pérez-Suay, Fatih Nar, Gustau Camps-Valls
In this work we propose a method to find anomalous changes in remote sensing images based on the chronochrome approach.
no code implementations • 7 Dec 2020 • Fatih Nar, Erdal Yilmaz, Gustau Camps-Valls
We here introduce an automatic Digital Terrain Model (DTM) extraction method.
no code implementations • 7 Dec 2020 • José A. Padrón Hidalgo, Adrián Pérez-Suay, Fatih Nar, Gustau Camps-Valls
In this letter, we propose two families of techniques to improve the efficiency of the standard kernel Reed-Xiaoli (RX) method for anomaly detection by approximating the kernel function with either {\em data-independent} random Fourier features or {\em data-dependent} basis with the Nystr\"om approach.
no code implementations • 15 Jan 2018 • Fatih Nar
Speckle noise, inherent in synthetic aperture radar (SAR) images, degrades the performance of the various SAR image analysis tasks.
no code implementations • 2 Oct 2016 • Atilla Ozgur, Hamit Erdem, Fatih Nar
In the proposed method, ensemble weights finding problem is modeled as a cost function with the following terms: (a) a data fidelity term aiming to decrease misclassification rate, (b) a sparsity term aiming to decrease the number of classifiers, and (c) a non-negativity constraint on the weights of the classifiers.