Biometrics image denoising algorithm based on contourlet transform

Authors:
Monika Godzwon;Khalid Saeed
Affiliations:
Faculty of Physics and Applied Computer Science, AGH University of Science and Technology, Kraków, Poland;Faculty of Physics and Applied Computer Science, AGH University of Science and Technology, Kraków, Poland
Venue:
ICCVG'12 Proceedings of the 2012 international conference on Computer Vision and Graphics
Year:
2012

Citing 5
Cited 0

Finger vein pattern extraction algorithm

HAIS'11 Proceedings of the 6th international conference on Hybrid artificial intelligent systems - Volume Part I
Image Denoising Algorithm Using Neighbourhood Characteristics and Cycle Spinning

ICDMA '11 Proceedings of the 2011 Second International Conference on Digital Manufacturing & Automation
The curvelet transform for image denoising

IEEE Transactions on Image Processing
Sparse geometric image representations with bandelets

IEEE Transactions on Image Processing
The contourlet transform: an efficient directional multiresolution image representation

IEEE Transactions on Image Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents a new image denoising method based on contourlet transform and Lee filter. Classical contourlet transform methods are based on denoising procedure that processes the contourlet coefficients with a threshold in each subband. This is performed without considering the neighbourhood characteristics of the invariance of the contourlet transform which introduces some artifacts. In this work, however, Lee filter is used to solve this problem. The suggested algorithm is particularly useful when considering biometric images that need precise preprocessing.