Suleyman Demirci

We don’t have enough information about this author to calculate their statistics. If you think this is an error let us know.
Learn More
The spectral matching, statistical and kernel based methods are the most widely known classification algorithms for hyperspectral imaging. Spectral matching algorithms try to identify the similarity of the unknown spectral signature of test pixels with the expected signature. In this study, an efficient spectral similarity method employing Multi-Scale(More)
Abstract. In this study, an efficient spectral similarity method referred to as Weighted Chebyshev Distance (WCD) method is introduced for supervised classification of hyperspectral imagery (HSI) and target detection applications. The WCD is based on a simple spectral similarity based decision rule using limited amount of reference data. The estimation of(More)
  • 1