• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.1186-1191
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• 1991

This paper represents a new edge relaxation algorithm that enhances the noisy boundary informations in images. The proposed algorithm employes relaxation process that reduces or eliminates ambiguities of derivative operator response via contextual informations. The contextual informations are the neighborhood patterns of a central edge which are estimated using fuzzy pattern matching technique. The algorithm is developed on crack edges. Experimental results show that the proposed scheme is effective even for noisy images or low contrast images.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.588-591
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• 2009

This paper proposes a reversible information hiding method for binary images. A half of pixels in noisy blocks on cover images is candidate for embeddable pixels. Among the candidate pixels, we select compressive pixels by bit patterns of its neighborhood to compress the pixels effectively. Thus, embeddable pixels in the proposed method are compressive pixels in noisy blocks. We provide experimental results using several binary images binarized by the different methods.

• Journal of the Korea Society of Computer and Information
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• v.11 no.4 s.42
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• pp.9-15
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• 2006

In this paper we propose Wilcoxon test, Median test and Van der Waerden test such as linear rank tests in two-sample location problem for detecting edges effectively in noisy images. These methods are based on detecting image intensity changes between two pixel neighborhoods using an edge-height model to perform effectively on noisy images. The neighborhood size used here is small and its shape is varied adaptively according to edge orientations. We compare and analysis the performance of these statistical edge detectors on both natural images and synthetic images with and without noise.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.149-152
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• 2003

This paper presents a method to find motion vectors that are closer to true motion with noisy images for simultaneous noise reduction and do-interlacing. The proposed method requires four interlaced field images: one noisy field image and three field images from which noise is already removed. The validation of motion provides accurate motion vectors and allows us to utilize them even in very noisy environment. The validated motion vectors are first used for the noise reduction, buffered and used later for the noise reduction and de -interlacing.

• 한국데이터정보과학회:학술대회논문집
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• 2004.04a
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• pp.197-201
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• 2004

We describe a new edge detector based on the robust rank-order (RRO) test which is a useful alternative to Wilcoxon test, using $r{\times}r$ window for detecting edges of all possible orientations in noisy images. Some experiments of statistical edge detectors based on the Wilcoxon test and T test with our RRO detector are carried out on synthetic and real images corrupted by both Gaussian and impulse noise. We also implement these edge detectors using Java on the Web.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1392-1394
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• 1996

This paper presents an algorithm to separate vowels from consonants in Korean characters captured in noisy images and to recognize them. The algorithm has been originally developed for the recognition of the usage code (which is represented by a single Korean character) in the license plates or Korean vehicles. It, however, could be easily adopted to other applications with minor changes, in which character recognition is needed and the environment is noisy. The key ideas or the algorithm are to localize the vowels utilizing the Hough transformation and to separate the vowels from consonants utilizing mathematical morphology. We observed that the presented algorithm effectively separates vowels even if the vowels and consonants are joined together after thresholding. We also observed that our algorithm outperforms some conventional algorithms especially when the input images are noisy. The details of the comparison study are presented in the paper.

• The Korean Journal of Applied Statistics
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• v.14 no.1
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• pp.149-160
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• 2001

In this paper we employ two-sample location tests such as Wilcoxon test and T test for detecting edges in noisy images. For this, we compute a test statistic on pixel gray levels obtained using an edge-height parameter and compare it with a threshold determined by a significance level. Experimental results applied to sample images are given and performances of these tests in terms of the objective measure are compared.

• Journal of radiological science and technology
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• v.46 no.6
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• pp.475-484
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• 2023

This study aimed to compare filters for reducing speckle noise in ultrasound images using clinical liver images. We acquired the clinical liver ultrasound images, and noisy images were obtained by adding 0.01, 0.05, 0.10, and 0.50 intensity levels of speckle noise to the liver images. The Wiener filter, median modified Wiener filter, gamma filter, and Lee filter were designed for the noisy images by setting window sizes at 3×3, 5×5, and 7×7. The coefficient of variation (COV) and contrast to noise ratio (CNR) were calculated to evaluate noise reduction and various filters. Moreover, the filter with the highest image quality was selected and quantitatively compared to a noisy image. As a result, COV and CNR showed the noise improved result when the Lee filter was applied. Furthermore, the Lee filter image with a window size of 7×7 was noted to possess approximately a minimum of 1.28 to a maximum of 3.38 times better COV and a minimum of 2.18 to a maximum of 5.50 times better CNR than the noisy image. In conclusion, we confirmed that the Lee filter was effective in reducing speckle noise and proved that an appropriate window size needs to be set considering blurring.

• The Journal of the Acoustical Society of Korea
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• v.17 no.1E
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• pp.30-35
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• 1998

Given a noisy sampled at equispaced points with white noise, we consider problems where the signal to be recovered is known to be positive; for example, images, chemical spectra or other measurements of intensities. Shrinking noisy wavelet coefficients via thresholding offers very attractive alternatives to existing methods of recovering signals from noisy data. In this paper, we propose a method of recovering the original signal from a corrupted noisy signal, guaranteeing the recovered signal positive. We first obtain wavelet coefficients by thresholding, and use a nonlinear optimization to find the denoised signal which must be positive. Numerical examples are used to illustrate the performance of the proposed algorithm.

• The Korean Journal of Applied Statistics
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• v.20 no.1
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• pp.147-157
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• 2007

Edge detection has been widely used in computer vision and image processing. We describe a new edge detector based on the robust rank-order test which is a useful alternative to Wilcoxon test. Our method is based on detecting pixel intensity changes between two neighborhoods with a $r{\times}r$ window using an edge-height model to perform effectively on noisy images. Some experiments of our robust rank-order detector with several existing edge detectors are carried out on both synthetic images and real images with and without noise.