Paper
26 October 2013 Robust multi-scale edge detection for noisy images
Author Affiliations +
Proceedings Volume 8917, MIPPR 2013: Multispectral Image Acquisition, Processing, and Analysis; 891717 (2013) https://doi.org/10.1117/12.2034306
Event: Eighth International Symposium on Multispectral Image Processing and Pattern Recognition, 2013, Wuhan, China
Abstract
Natural images often suffer from common problem of poor resolution and low SNR. However, conventional methods can’t accurately detect the edge for this type of images. In this paper, we present a robust multi-scale edge detection algorithm for noisy images. Firstly, we down-sample the image to multi-scale resolution, and then the edge features are exacted with the improved difference eigenvalue algorithm. Finally, the multi-scale edges are combined to the accurate edge using the method of Improved New Edge Direction Interpolation (INEDI). Experimental results show that the proposed method outperforms the conventional methods while suppressing noise and preserving edge thus is suited for nature images edge detection.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yongsheng Wang and Nong Sang "Robust multi-scale edge detection for noisy images", Proc. SPIE 8917, MIPPR 2013: Multispectral Image Acquisition, Processing, and Analysis, 891717 (26 October 2013); https://doi.org/10.1117/12.2034306
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KEYWORDS
Edge detection

Image resolution

Signal to noise ratio

Dubnium

Motion models

Image processing

Image segmentation

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