• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.3
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• pp.49-58
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• 2020

Image interpolation, a technology that converts low resolution images into high resolution images, has been widely used in various image processing fields such as CCTV, web-cam, and medical imaging. This technique is based on the fact that the statistical distributions of the white Gaussian noise and the difference between the interpolated image and the original image is similar to each other. The proposed algorithm is composed of three steps. In first, the interpolated image is derived by random image interpolation. In second, we derive weighting functions that are used to apply non-local mean filtering. In the final step, the prediction error is corrected by performing non-local mean filtering by applying the selected weighting function. It can be considered as a post-processing algorithm to further reduce the prediction error after applying an arbitrary image interpolation algorithm. Simulation results show that the proposed method yields reasonable performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.9C
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• pp.555-563
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• 2011

In this paper, we propose an object based 2D image to 3D conversion algorithm by using motion estimation, color labeling and non-local mean filtering methods. In the proposed algorithm, we first extract the motion vector of each object by estimating the motion between frames and then segment a given image frame with color labeling method. Then, combining the results of motion estimation and color labeling, we extract object regions and assign an exact depth value to each object to generate the right image. While generating the right image, occlusion regions occur but they are effectively recovered by using non-local mean filter. Through the experimental results, it is shown that the proposed algorithm performs much better than conventional conversion scheme by removing the eye fatigue effectively.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.159-162
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• 2008

This paper presents a modified mean curvature diffusion filter to smooth speckle noise in images. Mean curvature diffusion filter has already shown good results in reducing noise in images while preserving fine details. In the mean curvature diffusion, the rate of smoothing is controlled by the local value of the diffusion coefficient chosen to be a function of the local image gradient magnitude. In this paper, the diffusion coefficient is modified to be controlled adaptively by local image surface slope and heterogeneity. The local surface slope contributes to preserving details (e.g.edges) in image and the local surface heterogeneity helps the smoothing filter consider the amount of noise in both edge and non-edge area. The proposed filter's performance is demonstrated by quantitative experiments using speckle noised aerial image and TerraSAR-X satellite image.

• Journal of applied mathematics & informatics
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• v.27 no.3_4
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• pp.909-913
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• 2009

For a family of graphs $\mathcal{H}$ and an integer k, we denote by $R^k(\mathcal{H})$ the corresponding k-Ramsey number, which is defined to be the smallest integer n such that every k-coloring of the edges of $K_n$ contains a monochromatic copy of a graph in $\mathcal{H}$. The local k-Ramsey number $R^k_{loc}(\mathcal{H})$ and the mean k-Ramsey number $R^k_{mean}(\mathcal{H})$ are defined analogously. Let $\mathcal{G}$ be the family of non-bipartite graphs and $T_n$ be the family of all trees on n vertices. In this paper we prove that $R^k_{loc}(\mathcal{G})=R^k_{mean}(\mathcal{G})$, and $R^2(T_n)$ < $R^2_{loc}(T_n)4 = $R^2_{mean}(T_n)$ for all $n\;{\ge}\;3$.

• KIISE Transactions on Computing Practices
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• v.20 no.11
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• pp.573-578
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• 2014

In this letter, we propose a noise reduction method for use in magnetic resonance images that is based on non-local mean and guided image filters. Our method consists of two phases. In the first phase, the guidance image is obtained from a noisy image by using an adaptive non-local mean filter. The spread of the kernel is adaptively by controlled by implementing the concept of edgeness. In the second phase, the noisy images and the guidance images are provided to the guided image filter as input in order to produce a noise-free image. The improved performance of the proposed method is investigated by conducting experiments on standard datasets that contain magnetic resonance images. The results show that the proposed scheme is superior over the existing approaches.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.5
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• pp.323-330
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• 2019

Radiometric normalization with multi-temporal satellite images is essential for time series analysis and change detection. Generally, relative radiometric normalization, which is an image-based method, is performed, and histogram matching is a representative method for normalizing the non-linear properties. However, since it utilizes global statistical information only, local information is not considered at all. Thus, this paper proposes a histogram matching method considering local information. The proposed method divides histograms based on density, mean, and standard deviation of image intensities, and performs histogram matching locally on the sub-histogram. The matched histogram is then further partitioned and this process is performed again, iteratively, controlled with the wasserstein distance. Finally, the proposed method is compared to global histogram matching. The experimental results show that the proposed method is visually and quantitatively superior to the conventional method, which indicates the applicability of the proposed method to the radiometric normalization of multi-temporal images with non-linear properties.

• Journal of Fashion Business
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• v.3 no.1
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• pp.125-137
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• 1999

The present study aims to reveal the sweating reaction of male adults, focused on athletes. With six subjects (3 athletes and 3 non-athletes) in two different conditions of ambient temperature (I : $25\pm1.0^{\circ}C$, II : $29.5\pm1.0^{\circ}C$), their total sweat rate, local sweat rate, skin temperature, physiological reaction (rectal temperature, blood pressure, and pulse rate), and psychological reaction (thermal, moisture, comfort, and perceptive sweat sensations) were measured. The comparison gave the following results: Total sweating rate was greater in non-athletes, while the two groups had more perspiration in ambience II. Local sweating rate in both ambiences was the greatest in the central breast area (athletes) and the infrascapular area (non-athletes). The mean skin temperature had more changes of increase and decrease in athletes. As to physiological reaction, non-athletes had lower rectal temperature and blood pressure as well as higher pulse rate. As for psychological reaction in Ambience II, the 4 sensations were mostly 'hot', 'humid', 'uncomfortable', and 'sweaty'.

• Journal of applied mathematics & informatics
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• v.17 no.1_2_3
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• pp.509-517
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• 2005

We shall prove the existence and uniqueness theorem of a solution to the non local fuzzy differential equation using the contraction mapping principle.

• Plant Resources
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• v.3 no.3
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• pp.200-205
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• 2000

This study selects Sunwol local group, Gusang local group and Yongjun local group to examine the appropriate amount of applied fertilizer in cultivating the double crop seed of Alisma plantago by transplantation in the southern area, improve and complements the double cropping techniques and contribute to stable production. While the plant height is 45,47 and 49cm and the number of leaves is 11.7, 12.5 and 14.4 at non-fertilizing plot, the plant height is 67, 72 and 75cm and the number of leaves is 15.8, 17.2 and 19.3 at all fertilizing plot and their growth is active and in the character of plant height and the number of leaves, especially in the groove of N-P$_{2}$O$_{5}$-K$_{2}$O= 30-15-45kg/10a, the mean plant height of Sunwol is 75cm and mean number of its leaves is 19.3, the mean plant height and number of leaves in Gusang are 72cm and 17.2 respectively and those of Yongjun are 67cm and 15.8 respectively. While the number of floral axis is 1,2 in non-fertilizing plot, that of the whole varieties in all fertilizing plot is 3, 4, 5 and the mean floral axis of Sunwol is N-P$_{2}$O$_{5}$-K$_{2}$O = 10-5-15, 20-10-30, 30-15-45 kg/10a and 18-0-18 of complex fertilizer and 21-17-17kg/10a and it is small in all fertilizing plot. The yield of dry root per 10a is high in all fertilizing grooves and especially in the groove of N-P$_{2}$O$_{5}$-K$_{2}$O = 30-15-45 kg/10a, it is 372.6kg, in the groove of 18-0-18kg/10a using complex fertilizer, it is 389.1kg and in that of 21-17-17kg/10a, it is 376.7kg.6.7kg.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.2
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• pp.86-94
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• 2010

In this paper, we propose spatially adaptive color demosaicing of noisy Bayer data. When sensor noises are not considered in demosaicing, they may degrade result image. In order to obtain high resolution image, sensor noises are considered in the color demosaicing step. We identify flat, edge and pattern regions at each pixel location to improve the performance of the algorithm and to reduce complexity. Based on the pre-classified regions, the demosaicing of the G channel is performed using the local statistics to reduce the interpolation error. The sensor noise is simultaneously removed by a modified version of non-local mean filter in the green and in the color difference domain. The R and B channels are interpolated easily using fully interpolated and denoised G and color difference values. Experimental results show that the proposed method achieves a significant improvement in terms of visual and numerical criteria, when compared to conventional methods.