Review Article Open Access

BM3D Outperforms Major Benchmarks in Denoising: An Argument in Favor

Bhawna Goyal1, Ayush Dogra2 and Apoorav Maulik Sharma2
  • 1 Chandigarh University, India
  • 2 Panjab University, India


The inherent physical limitations of imaging sensors lead to prevalence of additive white Gaussian noise in images which deters the feature extraction and analysis. There exists a number of denoising algorithms in literature, demonstrating their efficacy for removing noise while preserving feature details. At the crossing of functional and statistical analysis, one argues with new methods being devised quite frequently, whether the decade old BM3D is still efficient or not. While carrying out extended experimentation and evaluation for removal of Gaussian noise from natural images in terms peak signal to noise ratio, an argument in favor of BM3D has been presented in this manuscript.

Journal of Computer Science
Volume 16 No. 6, 2020, 838-847


Submitted On: 14 April 2020 Published On: 1 July 2020

How to Cite: Goyal, B., Dogra, A. & Sharma, A. M. (2020). BM3D Outperforms Major Benchmarks in Denoising: An Argument in Favor. Journal of Computer Science, 16(6), 838-847.

  • 2 Citations



  • Denoising
  • PSNR
  • Shearlet
  • BM3D and Bitonic Filtering