By Topic

Research on Scale Selection in Image Edge Detection Methods Based on Wavelet Transform

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Huiyan Wang ; Coll. of Comput. Sci. & Inf. Eng., Zhejiang Gongshang Univ., Hangzhou, China

The actual images are often contaminated by noise. Noise reduction is the first step to image processing. But the noise reduction and edge localization are contradictory, which makes edge detection is an ill-posed problem. In multi-scale edge detection using wavelet transform (WT), the scale selection is one key problem. In small scale, edges can be localized accurately, but are sensitive to noise, while in large scale, noise can be suppressed effectively, but edges may deviate from original location. Edges can be detected exactly only when scale selected is a good compromise of these two factors. In this paper, seven edge types are modeled and the scale selection is analyzed for each type. According to the analytical results, some important rules are given, which can guide the scale selection of WT and provide theoretical basis for edge detection and noise reduction.

Published in:

Image and Signal Processing, 2009. CISP '09. 2nd International Congress on

Date of Conference:

17-19 Oct. 2009