Click for new scientific resources and news about Corona[COVID-19]

Paper Information

Journal:   IRANIAN JOURNAL OF ELECTRICAL AND ELECTRONIC ENGINEERING   JUNE 2016 , Volume 12 , Number 2; Page(s) 97 To 104.
 
Paper: 

A NEW SHEARLET HYBRID METHOD FOR IMAGE DENOISING

 
 
Author(s):  EHSAEYAN E.*
 
* DEPARTMENT OF ELECTRICAL ENGINEERING, SIRJAN UNIVERSITY OF TECHNOLOGY, SIRJAN, IRAN
 
Abstract: 

Traditional noise removal methods like Non-Local Means create spurious boundaries inside regular zones. Visushrink removes too many coefficients and yields recovered images that are overly smoothed. In Bayesshrink method, sharp features are preserved. However, PSNR (Peak Signal-to-Noise Ratio) is considerably low. BLS-GSM generates some discontinuous information during the course of denoising and destroys the flatness of homogenous area. Wavelets are not very effective in dealing with multidimensional signals containing distributed discontinuities such as edges. This paper develops an effective shearlet-based denoising method with a strong ability to localize distributed discontinuities to overcome this limitation. The approach introduced here presents two major contributions: (a) Shearlet Transform is designed to get more directional subbands which helps to capture the anisotropic information of the image; (b) coefficients are divided into low frequency and high frequency subband. Then, the low frequency band is refined by Wiener filter and the high-pass bands are denoised via NeighShrink model.
Our framework outperforms the wavelet transform denoising by %7.34 in terms of PSNR (peak signal-to-noise ratio) and %13.42 in terms of SSIM (Structural Similarity Index) for‘Lena’ image. Our results in standard images show the good performance of this algorithm, and prove that the algorithm proposed is robust to noise.

 
Keyword(s): IMAGE DENOISING, SHEARLET TRANSFORM, NEIGHSHRINK, WIENER FILTER, PSNR, SSIM, WAVELET, EDGE PRESERVING, THRESHOLD, SURESHRINK
 
 
References: 
  • Not Registered.
  •  
  •  
 
Citations: 
  • Not Registered.
 
+ Click to Cite.
APA: Copy

EHSAEYAN, E. (2016). A NEW SHEARLET HYBRID METHOD FOR IMAGE DENOISING. IRANIAN JOURNAL OF ELECTRICAL AND ELECTRONIC ENGINEERING, 12(2), 97-104. https://www.sid.ir/en/journal/ViewPaper.aspx?id=571817



Vancouver: Copy

EHSAEYAN E.. A NEW SHEARLET HYBRID METHOD FOR IMAGE DENOISING. IRANIAN JOURNAL OF ELECTRICAL AND ELECTRONIC ENGINEERING. 2016 [cited 2021August02];12(2):97-104. Available from: https://www.sid.ir/en/journal/ViewPaper.aspx?id=571817



IEEE: Copy

EHSAEYAN, E., 2016. A NEW SHEARLET HYBRID METHOD FOR IMAGE DENOISING. IRANIAN JOURNAL OF ELECTRICAL AND ELECTRONIC ENGINEERING, [online] 12(2), pp.97-104. Available: https://www.sid.ir/en/journal/ViewPaper.aspx?id=571817.



 
  pdf-File
Yearly Visit 34
 
 
Latest on Blog
Enter SID Blog