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22 July 1997 Comparison of Daubechies, Coiflet, and Symlet for edge detection
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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.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Rajeev Singh, Ramon E. Vasquez, and Reena Singh "Comparison of Daubechies, Coiflet, and Symlet for edge detection", Proc. SPIE 3074, Visual Information Processing VI, (22 July 1997);


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