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  Published Paper Details:

  Paper Title

ESTIMATION OF NOISE IN HYPERSPECTRAL REMOTE SENSING IMAGES USING CURVELET TRANSFORM

  Authors

  Thirumala Lakshmi K,  Mugambika,  Saraswathi,  Uchimakali

  Keywords

Hyper spectral image, denoise, wavelet transform, curvelet transform, threshold

  Abstract


In this paper, the author have attempted to estimate the noise in hyperspectral images over the belt of 350N to 350S and 1180E to 1180W from the satellite AVIRIS images obtained from JPL, NASA for the period October 1992. The paper aims in particular, to find out the thresholding technique and image transform for satellite image denoising. For this purpose the authors have investigated a few threshold techniques and wavelet transforms. The study shows that the curvelet transform is better than wavelet transform for noise estimation in hyperspectral images.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2101514

  Paper ID - 202807

  Page Number(s) - 4245-4255

  Pubished in - Volume 9 | Issue 1 | January 2021

  DOI (Digital Object Identifier) -    http://doi.one/10.1729/Journal.25715

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Thirumala Lakshmi K,  Mugambika,  Saraswathi,  Uchimakali,   "ESTIMATION OF NOISE IN HYPERSPECTRAL REMOTE SENSING IMAGES USING CURVELET TRANSFORM", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.9, Issue 1, pp.4245-4255, January 2021, Available at :http://www.ijcrt.org/papers/IJCRT2101514.pdf

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ISSN: 2320-2882
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ISSN and 7.97 Impact Factor Details


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ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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