SAR Image De-Noising based on GNL-Means with Optimized Pixel-Wise Weighting in Non-Subsample Shearlet Domain

  •  Shuaiqi Liu    
  •  Yu Zhang    
  •  Qi Hu    
  •  Ming Liu    
  •  Jie Zhao    


SAR images have been widely used in many fields such as military and remote sensing. So the suppression of the speckle has been an important research issues. To improve the visual effect of non-local means, generalized non-local (GNL) means with optimized pixel-wise weighting is applied to shrink the coefficients of non-subsample Shearlet transform (NSST) of SAR image. The new method can optimize the weight of GNL, which not only improve the PSNR of de-noised image, but also can significantly enhance the visual effect of de-noising image.

This work is licensed under a Creative Commons Attribution 4.0 License.
  • ISSN(Print): 1913-8989
  • ISSN(Online): 1913-8997
  • Started: 2008
  • Frequency: semiannual

Journal Metrics

WJCI (2022): 0.636

Impact Factor 2022 (by WJCI):  0.419

h-index (January 2024): 43

i10-index (January 2024): 193

h5-index (January 2024): N/A

h5-median(January 2024): N/A

( The data was calculated based on Google Scholar Citations. Click Here to Learn More. )