slugAn Efficient Objects Discrimination and Noise Reduction on Hyperspectral Images

Abstract

Hyperspectral imaging (HSI) combines conventional imaging and spectroscopy to attain both spatial and spectral information from an object. But the main drawback in HSI is inheritance of noise while their acquisition or transmission. The amount of noise included in a hyperspectral image limits its application and has a negative impact on hyperspectral image classification, discrimination, target detection, and so on. Denoising algorithm is Choice of application dependent and depends upon the type of noise present in the object. Every algorithm has its own assumptions, advantages and limitations. Here comparative analysis of various noise suppression algorithms of spatial noise reduction on hyperspectral images. Noise reduction will increase the performance of discrimination on hyperspectral images with Principal Component Analysis (PCA).

Authors and Affiliations

Sarath Babu, S. John Livingston

Keywords

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  • EP ID EP17792
  • DOI -
  • Views 385
  • Downloads 10

How To Cite

Sarath Babu, S. John Livingston (2014). slugAn Efficient Objects Discrimination and Noise Reduction on Hyperspectral Images. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 2(3), -. https://europub.co.uk./articles/-A-17792