Adaptive Medical Image Edge Detection in Contourlet Domain

Part of the IFMBE Proceedings book series (IFMBE, volume 49)

Abstract

Wavelet transforms and other frequency domain methods are widely used for edge detection, but they suffer from shift and rotation sensitivity. Recently, new x-let multiscale transforms have been developed. This paper describes a method for medical image edge detection in contourlet transform domain that uses cycle spinning. The edge detection is done by performing contourlet transform to the medical image, keeping the coefficients where the signal-to-noise ratio is high, and reducing the coefficients where the signal-to-noise ratio is low. For the contourlet transform to be translation-invariant a 2-D cycle spinning is implemented on subbands ∆ 1 and ∆ 2 . Cycle spinning for edge detection is implemented. The transformed data are shifted, edge detected and unshifted. The method has been compared with earlier edge detection methods that use the discrete wavelet transform and contourlet transform.

Keywords

medical image edge detection contourlet tranform cycle spinning 

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Copyright information

© IFMBE 2013

Authors and Affiliations

  1. 1.Faculty of Computer Science and EngineeringHo Chi Minh City University of TechnologyHo Chi Minh CityVietnam

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