Share Email Print

Proceedings Paper

Comparison of Daubechies, Coiflet, and Symlet for edge detection
Author(s): Rajeev Singh; Ramon E. Vasquez; Reena Singh
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

The ability of wavelets to extract the high frequency component of an image has made them useful for edge detection. The high frequency details are analyzed and processed to obtain the edges. This work is primarily concerned with the comparison of Daubechies, Coiflet, and Symlet wavelets for the purpose of edge detection. Discrete wavelet frame has been sued to detect edges in this work. Different wavelet filters of varied lengths have been used to find out the best wavelet for edge detection. The criterion chosen for comparison is the same threshold selection. The results of the experimentation suggest that the Haar wavelet, which is the simplest of the Daubechies wavelets, is the best wavelet with the methodology followed in this paper. The results are also indicative of the fact that with increase in filter length the performance of the wavelet deteriorates.

Paper Details

Date Published: 22 July 1997
PDF: 9 pages
Proc. SPIE 3074, Visual Information Processing VI, (22 July 1997); doi: 10.1117/12.280616
Show Author Affiliations
Rajeev Singh, Univ. of Puerto Rico/Mayaguez (United States)
Ramon E. Vasquez, Univ. of Puerto Rico/Mayaguez (United States)
Reena Singh, Univ. of Puerto Rico/Mayaguez (United States)

Published in SPIE Proceedings Vol. 3074:
Visual Information Processing VI
Stephen K. Park; Richard D. Juday, Editor(s)

© SPIE. Terms of Use
Back to Top