Title :
Use of the second-kind statistics for VHR SAR image retrieval
Author :
Singh, Jagmal ; Datcu, Mihai
Author_Institution :
Remote Sensing Technol. Inst. (IMF), German Aerosp. Center (DLR), Oberpfaffenhofen, Germany
Abstract :
The Method of Log Cumulants (MoLC) has been recently proposed for analysis and parameter estimation of the probability density function (pdf) defined in R+. Here the Fourier transform as the characteristics function is replaced with Mellin transform for parameter estimation. Instead of focusing on pdf parameter estimation using MoLC, our objective in this article is to directly use log-moments (also called second-kind moments in second-kind statistics) of transformed synthetic aperture radar (SAR) images as the feature descriptor describing the image content. Gabor filters have been considered to transform the SAR image data. Comparison is presented with first and higher-order statistics and spectral feature descriptors. K-nearest neighborhood (K-NN) classification algorithm have been used as classifier.
Keywords :
Gabor filters; feature extraction; image retrieval; parameter estimation; probability; radar imaging; synthetic aperture radar; transforms; Fourier transform; Gabor filter; K-NN classification algorithm; K-nearest neighborhood; Mellin transform; MoLC; SAR images; VHR SAR image retrieval; feature extraction; image content; log-moment; method of log cumulant; pdf parameter estimation; probability density function; spectral feature descriptors; very high-resolution synthetic aperture radar; Accuracy; Computational modeling; Feature extraction; Mathematical model; Parameter estimation; Synthetic aperture radar; Training; Gabor filter; Very high-resolution synthetic aperture radar (VHR SAR); feature extraction; log-moments;
Conference_Titel :
Communications (COMM), 2012 9th International Conference on
Conference_Location :
Bucharest
Print_ISBN :
978-1-4577-0057-6
DOI :
10.1109/ICComm.2012.6262556