Noise Removal and Edge Detection of Image by Image Structure Understanding


The Transactions of the Korea Information Processing Society (1994 ~ 2000), Vol. 4, No. 7, pp. 1865-1872, Jul. 1997
10.3745/KIPSTE.1997.4.7.1865,   PDF Download:

Abstract

This paper proposes not only the thresholding problem which has been one of the major problems in the pre-existing edge detection method but also the removal of blurring effect occurred at the edge regions due to the smoothing process. The structure of a given image is assigned as one of the three predefined image structure classes by evaluating its toll membership value to each reference structure class : The structure of an image belongs to the structure class which has the least cost value with the image. Upon the structure class assigned, noise removal and edge extraction precesses are performed, e.g., the smoothing algorithm is applied to the image if its structure belongs to the pure noise region class; edge extraction while removing the noise is performed simultaneously if the edge structure class. The proposed method shows that preventing the blurring effect can be usually seen in the edge images and extracting the edges with no using thresholding value by the experiments.


Statistics
Show / Hide Statistics

Statistics (Cumulative Counts from September 1st, 2017)
Multiple requests among the same browser session are counted as one view.
If you mouse over a chart, the values of data points will be shown.


Cite this article
[IEEE Style]
C. D. Uk, "Noise Removal and Edge Detection of Image by Image Structure Understanding," The Transactions of the Korea Information Processing Society (1994 ~ 2000), vol. 4, no. 7, pp. 1865-1872, 1997. DOI: 10.3745/KIPSTE.1997.4.7.1865.

[ACM Style]
Cho Dong Uk. 1997. Noise Removal and Edge Detection of Image by Image Structure Understanding. The Transactions of the Korea Information Processing Society (1994 ~ 2000), 4, 7, (1997), 1865-1872. DOI: 10.3745/KIPSTE.1997.4.7.1865.