ARTICLE
TITLE

Noise Robust Hyperspectral Image Classification With MNF-Based Edge Preserving Features

 Articles related

M. Balasco,D. Chianese,G. Di Bello,M. R. Gallipoli,V. Lapenna    

n this work we present the main features of a new multiparametric station able to jointly detect self-potential and seismometric signals in a seismic active area of Southern Italy. The new station has been designed and installed at the Tito Laboratories ... see more


M. Kopecký    

During the last decade, Zhaohua Wu and Norden E. Huang announced a new improvement of the original Empirical Mode Decomposition method (EMD). Ensemble Empirical Mode Decomposition and its abbreviation EEMD represents a major improvement with great versat... see more


J. Rajnoha    

Automatic speech recognition (ASR) systems frequently work in a noisy environment. As they are often trained on clean speech data, noise reduction or adaptation techniques are applied to decrease the influence of background disturbance even in the case o... see more


Di Guo, Zhangren Tu, Jiechao Wang, Min Xiao, Xiaofeng Du and Xiaobo Qu    

Images may be corrupted by salt and pepper impulse noise during image acquisitions or transmissions. Although promising denoising performances have been recently obtained with sparse representations, how to restore high-quality images remains challenging... see more

Revista: Algorithms

Sornkitja Boonprong, Chunxiang Cao, Wei Chen, Xiliang Ni, Min Xu and Bipin Kumar Acharya    

Remotely sensed data are often adversely affected by many types of noise, which influences the classification result. Supervised machine-learning (ML) classifiers such as random forest (RF), support vector machine (SVM), and back-propagation neural netwo... see more