A fast method for image noise estimation using laplacian operator and adaptive edge detection

Research output: Chapter in Book/Report/Conference proceedingConference contribution

116 Citations (Scopus)

Abstract

We present a simple and fast algorithm for image noise estimation. The input image is assumed to be corrupted by additive zero mean Gaussian noise. To exclude structures or details from contributing to the noise variance estimation, a simple edge detection algorithm using first-order gradients is applied first. Then a Laplacian operator followed by an averaging over the whole image will provide very accurate noise variance estimation. There is only one parameter which is self-determined and adaptive to the image contents. Simulation results show that the proposed algorithm performs well for different types of images over a large range of noise variances. Performance comparisons against other approaches are also provided.

Original languageEnglish
Title of host publication2008 3rd International Symposium on Communications, Control, and Signal Processing, ISCCSP2008
Pages1077-1081
Number of pages5
DOIs
Publication statusPublished - 2008 Sep 5
Event2008 3rd International Symposium on Communications, Control, and Signal Processing, ISCCSP2008 - St. Julians, Malta
Duration: 2008 Mar 122008 Mar 14

Publication series

Name2008 3rd International Symposium on Communications, Control, and Signal Processing, ISCCSP 2008

Other

Other2008 3rd International Symposium on Communications, Control, and Signal Processing, ISCCSP2008
CountryMalta
CitySt. Julians
Period08-03-1208-03-14

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All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics
  • Signal Processing
  • Control and Systems Engineering

Cite this

Tai, S-C., & Yang, S-M. (2008). A fast method for image noise estimation using laplacian operator and adaptive edge detection. In 2008 3rd International Symposium on Communications, Control, and Signal Processing, ISCCSP2008 (pp. 1077-1081). [4537384] (2008 3rd International Symposium on Communications, Control, and Signal Processing, ISCCSP 2008). https://doi.org/10.1109/ISCCSP.2008.4537384