• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.1
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• pp.8-16
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• 2011

Image inpainting is a technique for removing damaged regions and reconstructing them with visually plausible backgrounds. However, if size of the damaged regions for reconstructing is large, the unexpected results can be obtained due to disconnected structures within reconstructed regions. In this paper, by considering spatial distance information between candidate patches and a damaged patch as well as pixel value difference, an exemplar-based image inpainting using multiple patches is proposed. In conventional exemplar-based image inpainting method, implausible results such as blocking effects or repetition of reconstructed patch may occur by using inappropriately selected single patch. To improve the exemplar-based method, the weighted sum of multiple patches considering both the spatial distance and the pixel value difference between the target patch and the candidate patches is utilized. Experimental results have shown that the proposed method produces better performance of image inpainting than the existing method.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.2
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• pp.16-28
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• 2004

A seam-line determination algorithm is proposed to determine image border-line in mosaicing using the transformation of gray value differences and dynamic programming. Since visually good border-line is the one along which pixel differences are as small as possible, it can be determined in association with an optimal path finding algorithm. A well-known effective optimal path finding algorithm is the Dynamic Programming (DP). Direct application of the dynamic programming to the seam-line determination causes the distance effect, in which seam-line is affected by its length as well as the gray value difference. In this paper, an adaptive cost transform algorithm with which the distance effect is suppressed is proposed in order to utilize the dynamic programming on the transformed pixel difference space. Also, a figure of merit which is the summation of fixed number of the biggest pixel difference on the seam-line (SFBPD) is suggested as an evaluation measure of seamlines. The performance of the proposed algorithm has been tested in both quantitively and visually on various kinds of images.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.6 s.312
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• pp.92-100
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• 2006

In imaging devices such as digital cameras using a single image sensor, captured images are the sub-sampled images comprised of the pixels that have only one of the three primary colors per a pixel. This images should be restored to the color images through an image processing referred as color interpolation. In this paper, we derive relation between the average of the data from CFA image sensor and the average of each color channel data. By using this relation, a new efficient method for color interpolation is proposed. Also, in order to reduce the zipper effect in a restored image, missing luminance values are interpolated along any edges in the captured image. On the other hand, for the chrominance channel interpolation, we average difference between a chrominance value and a luminance value in a local area, and this average value is added to the pixel value of the interpolated location. The proposed method has been compared with several previous methods, and our experimental results show the better results than the other methods.

• Journal of the Korean Society of Radiology
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• v.15 no.3
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• pp.293-299
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• 2021

In order to reduce the irresistible radiation exposure of patients who perform periodic examinations using a CT among various scan parameters a method to reduce patient dose was investigated through changes in the tube voltage close to X-ray penetrating power. As a result of the experiment 100 kVp was applied instead of 120 kVp which is commonly used in clinical practice and CTDI decreased by about 41% during scan. In addition the degree of change in image quality was measured as 1046.1±3.7 HU for CT value and 71.4±7.9 for Pixel value and statistical analysis showed no significant difference (0.05

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.6
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• pp.79-84
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• 2015

In a distribution of digital image, there is a serious problem that is a distribution of the altered image by a forger. For the problem solution, this paper proposes a median filtering (MF) image forensic decision algorithm using a feature vector according to the pixel value's gradients. In the proposed algorithm, AR (Autoregressive) coefficients are computed from pixel value' gradients of original image then 1th~6th order coefficients to be six feature vector. And the reconstructed image is produced by the solution of Poisson's equation with the gradients. From the difference image between original and its reconstructed image, four feature vector (Average value, Max. value and the coordinate i,j of Max. value) is extracted. Subsequently, Two kinds of the feature vector combined to 10 Dim. feature vector that is used in the learning of a SVM (Support Vector Machine) classification for MF (Median Filtering) detector of the altered image. On the proposed algorithm of the median filtering detection, compare to MFR (Median Filter Residual) scheme that had the same 10 Dim. feature vectors, the performance is excellent at Unaltered, Averaging filtering ($3{\times}3$) and JPEG (QF=90) images, and less at Gaussian filtering ($3{\times}3$) image. However, in the measured performances of all items, AUC (Area Under Curve) by the sensitivity and 1-specificity is approached to 1. Thus, it is confirmed that the grade evaluation of the proposed algorithm is 'Excellent (A)'.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.7
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• pp.1399-1404
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• 2004

The development of computer technology and the advancement of the technology of information and communications spread the technology of multimedia and increased the use of multimedia data with large capacity. Users can grasp the overall video data and they are able to play wanted video back. To grasp the overall video data it is necessary to offer the list of summarized video data information. In order to search video efficiently an index process of video data is essential and it is also indispensable skill. Therefore, this thesis suggested the effective method about the cut detection of frames which will become a basis of an index based on contents of video image data. This suggested method was detected as the unchanging pixel rotor intelligence value, classified into diagonal direction. Pixel value of color detected in each frame of video data is stored as A(i, i) matrix - i is the number of frames, i is an image height of frame. By using the stored pixel value as the method of UE(Mean Square Error) I calculated a specified value difference between frames and detected cut quickly and exactly in case it is bigger than threshold value set in advance. To carry out an experiment on the cut detection of lames comprehensively, 1 experimented on many kinds of video, analyzing and comparing efficiency of the cut detection system.

• The Korean Journal of Nuclear Medicine Technology
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• v.15 no.2
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• pp.13-20
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• 2011

Purpose: The limited FOV(Field of View) of CT (Computed Tomography) can cause truncation artifact at external DFOV (Display Field of View) in PET/CT image. In our study, we measured the difference of SUV and compared the influence affecting to the image reconstructed with the extended DFOV. Materials and Methods: NEMA 1994 PET Phantom was filled with $^{18}F$(FDG) of 5.3 kBq/mL and placed at the center of FOV. Phantom images were acquired through emission scan. Shift the phantom's location to the external edge of DFOV and images were acquired with same method. All of acquired data through each experiment were reconstructed with same method, DFOV was applied 50 cm and 70 cm respectively. Then ROI was set up on the emission image, performed the comparative analysis SUV. In the clinical test, patient group shown truncation artifact was selected. ROI was set up at the liver of patient's image and performed the comparative analysis SUV according to the change of DFOV. Results: The pixel size was increase from 3.91 mm to 5.47 mm according to the DFOV increment in the centered location phantom study. When extended DFOV was applied, $_{max}SUV$ of ROI was decreased from 1.49 to 1.35. In case of shifted the center of phantom location study, $_{max}SUV$ was decreased from 1.30 to 1.20. The $_{max}SUV$ was 1.51 at the truncated region in the extended DFOV. The difference of the $_{max}SUV$ was 25.9% higher at the outside of the truncated region than inside. When the extended DFOV was applied, $_{max}SUV$ was decreased from 3.38 to 3.13. Conclusion: When the extended DFOV was applied, $_{max}SUV$ decreasing phenomenon can cause pixel to pixel noise by increasing of pixel size. In this reason, $_{max}SUV$ was underestimated. Therefore, We should consider the underestimation of quantitative result in the whole image plane in case of patient study applied extended DFOV protocol. Consequently, the result of the quantitative analysis may show more higher than inside at the truncated region.

• International Journal of Advanced Culture Technology
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• v.4 no.3
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• pp.48-55
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• 2016

Conventional techniques for solving the noise problem have problems to generate different results, depending on the image size and weight values of the used masks, and they require many operations by using a complex formula. In this paper, we propose an image enhancement algorithm to solve the noise problem in a simple, yet easy-to-use way. For this purpose, we determined the difference between the noise of the two adjacent pixels for the horizontal and vertical, and for the two diagonal directions that each of the noise problem occurred, and then we got the average value of these pixel values. Then, we solve the noise problem by using the optimal average value in accordance with occurrence of the noise in the horizontal and vertical, and two adjacent pixels in a diagonal direction. As a result, we got the result that the noise solution in a simple, yet easy-to-use method to obtain a resultant image.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.3
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• pp.504-509
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• 1987

In this paper a characteristics of image which can be segmented based on the thresholding technique using a histogram was investigated employing 3 parameters: the variance of pixel value, the average mean difference between target and background and the target size. The threshold value for the histogram segmentation was determined by applying the hypothesis testing theory. The performance of the selected threshold was evaluated by computing a probability of error. Since a priori probability can be easily obtained from the histogram, it was found that the Bayes decision rule which theoretically guarantees the minimum probability of error works better than the minimax criterion rule.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.612-615
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• 2003

The error diffusion is a good method to reconstruct the continuous tones of an image to the bilevel tones However the reconstruction of edge characteristic by the nor diffusion is represented work when power spectrum is analyzed fer display error. In this paper, we present an edge enhanced error diffusion method to preprocess original image to achieve the enhancement for the edge characteristic. The preprocessing algorithm consist of two processes. First the difference value between the current pixel and the local average of the surrounding pixel in original image is obtained. Second, the weighting function is composed by the magnitude and the sign of the local average. To confirm the effect of the proposed method, it is compared with the conventional edge enhanced error diffusion methods by measuring the radially averaged power spectrum densities (RAPSDs) for their display errors. The comparison result demonstrate the superiority of the proposed method over the conventional ones.