A design framework for hybrid approaches of image noise estimation and its application to noise reduction

  • Authors:

  • Shih-Ming Yang;Shen-Chuan Tai

  • Affiliations:

  • Department of Electrical Engineering, Institute of Computer and Communication Engineering, National Cheng Kung University, No. 1, University Rd., Tainan 701, Taiwan, ROC;Department of Electrical Engineering, Institute of Computer and Communication Engineering, National Cheng Kung University, No. 1, University Rd., Tainan 701, Taiwan, ROC

  • Venue:
  • Journal of Visual Communication and Image Representation
  • Year:
  • 2012

Quantified Score

Hi-index 0.00

Visualization

Abstract

Noise estimation is an important process in digital imaging systems. Many noise reduction algorithms require their parameters to be adjusted based on the noise level. Filter-based approaches of image noise estimation usually were more efficient but had difficulty on separating noise from images. Block-based approaches could provide more accurate results but usually required higher computation complexity. In this work, a design framework for combining the strengths of filter-based and block-based approaches is presented. Different homogeneity analyzers for identifying the homogeneous blocks are discussed and their performances are compared. Then, two well-known filters, the bilateral and the non-local mean, are reviewed and their parameter settings are investigated. A new bilateral filter with edge enhancement is proposed. A modified non-local mean filter with much less complexity is also present. Compared to the original non-local mean filter, the complexity is dramatically reduced by 75% and yet the image quality is maintained.