Title: Application of wavelet transform in edge detection
Abstract:Edge is the most important feature of an image. It contains much of information of an image. In addition, edge detection has a significant influence on the performance of image analysis and comprehens...Edge is the most important feature of an image. It contains much of information of an image. In addition, edge detection has a significant influence on the performance of image analysis and comprehension. In order to study the edge detection algorithm on the edge of the location and antinoise capability, we selected Log operator, Canny operator and wavelet transform edge detection algorithm to detect image edge by using Matlab software. Simulation results show that, three edge detection operators possessed different capacity in the edge location and suppress noise. Wavelet transform can provide the edge information of different scales. The experimental result shows that, since wavelet transform have a multi-scale feature and localization characteristic, it can accurately detect the edge points, In the meantime ,it can overcome preferably noise-sensitive problems which arise from Log operator and Canny operator .Read More
Publication Year: 2011
Publication Date: 2011-10-01
Language: en
Type: article
Indexed In: ['crossref']
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Cited By Count: 8
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Title: $Application of wavelet transform in edge detection
Abstract: Edge is the most important feature of an image. It contains much of information of an image. In addition, edge detection has a significant influence on the performance of image analysis and comprehension. In order to study the edge detection algorithm on the edge of the location and antinoise capability, we selected Log operator, Canny operator and wavelet transform edge detection algorithm to detect image edge by using Matlab software. Simulation results show that, three edge detection operators possessed different capacity in the edge location and suppress noise. Wavelet transform can provide the edge information of different scales. The experimental result shows that, since wavelet transform have a multi-scale feature and localization characteristic, it can accurately detect the edge points, In the meantime ,it can overcome preferably noise-sensitive problems which arise from Log operator and Canny operator .