• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.807-810
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• 2013

In this paper, a new technique for image enhancement using weighted cross-shaped median filter with edge-detection algorithm is proposed. It consists of simple hypothesis test for edge-detection, and makes use of the cross-shaped moving window. This method is applied to noise corrupted image and its results are compared with those of median filters. As for the experimental result, method of weighted cross-shaped median filter is superior to other median filters.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.1006-1009
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• 2013

In this paper, a new technique for image enhancement using cross-shaped median filter with edge-detection algorithm is proposed. It consists of simple hypothesis test for edge-detection, and makes use of the cross-shaped window. This method is applied to noise corrupted image and its results are compared with those of median filters. As for the experimental result, method of cross-shaped median filter is superior to other median filters.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.711-714
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• 2015

A new technique for image restoration using Weighted cross-shaped median filter with edge-detection algorithm is proposed in this paper. It consists of simple hypothesis test for edge-detection, and makes use of the weighted cross-shape window. This method is applied to noise corrupted image and its results are compared with those of median filters. As for the experimental result, method of weighted cross-shape median filter is superior to other median filters.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.2
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• pp.202-207
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• 2021

One of the most important tasks in image processing is noise filtering. Noise removal in image is a difficult task due to many reasons such as nonstationary sequences and corrupted by various types of noise. Human's visual perception is heavily based on the edge information. Thus, noise filtering must preserve edges. To remove the noise, we usually use the square-shaped median filter. They possess mathematical simplicity but have the disadvantages that blur the edges. In this paper we consider a new technique for image restoration using a weighted octagonal median filter. The technique consists of simple hypothesis test for edge detection, and we use the weighted octagonal-shaped moving window. The new technique is applied to noise corrupted image and experimental results are compared to the results of the square-shaped median filter and the cross-shaped median filter.