• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.195-208
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• 2004

Histogram is a very useful method on various practical aspect. With increasing importance of simple calculation method and convenience, it became the basic method in digital image processing nowadays. However, basic limit of using histogram is losing spatial position information of pixels on image. This paper reanalyzes image by presenting histogram with spatial position information(spatial histogram). Also using that result, level order recursive median filter is realized. Presented recursive median filter showed much improved results on edge maintenance aspect compared to existing recursive median filter.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.3
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• pp.698-704
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• 2013

The image process for image enhancement applies differently the same algorithm for each application. So, the optimized value for each application is required. In this paper, the X-ray medical image using a high-pass filter was improved edges. The result image was improved edge and the contrast of flat area using a constant multiplier and offset. Therefore, the high-frequency emphasis filter optimized for medical image is required. These optimized values are the gaussian high-pass filter, the distance of cutoff frequency=0.05 and offset=0.5. From the result of optimaized simulation, The proposed method has enhanced contrast and edge of the image in the contrast of existing mothods.

• Journal of information and communication convergence engineering
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• v.8 no.6
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• pp.645-650
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• 2010

In this paper, we present the effect of binocular cues which plays crucial role for the visualization of a stereoscopic or 3D image. This study is useful in extracting depth and disparity information by image processing technique. A linear relation between the object distance and the image distance is presented to discuss the cause of cybersickness. In the experimental results, three dimensional view of the depth map between the 2D images is shown. A median filter is used to reduce the noises available in the disparity map image. After the median filter, two filter algorithms such as 'Gabor' filter and 'Canny' filter are tested for disparity visualization between two images. The 'Gabor' filter is to estimate the disparity by texture extraction and discrimination methods of the two images, and the 'Canny' filter is used to visualize the disparity by edge detection of the two color images obtained from stereoscopic cameras. The 'Canny' filter is better choice for estimating the disparity rather than the 'Gabor' filter because the 'Canny' filter is much more efficient than 'Gabor' filter in terms of detecting the edges. 'Canny' filter changes the color images directly into color edges without converting them into the grayscale. As a result, more clear edges of the stereo images as compared to the edge detection by 'Gabor' filter can be obtained. Since the main goal of the research is to estimate the horizontal disparity of all possible regions or edges of the images, thus the 'Canny' filter is proposed for decipherable visualization of the disparity.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.684-688
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• 2009

In this paper, it proposes the technique to restore from a binary image in the color image. The color image is composed of three element images of red, green and blue. Therefore, the color image is first divided into a red, green, and blue element, and the Inverse Halftoning[2]$\sim$[4] is processed to each element images. Finally, each element images is collectively displayed. In that case, the Kalman filter was applied to the Inverse Halftoning for the restoration accuracy improvement of the image. As a result, it was possible to restore it in the color image as well as the time of a monochrome image. Moreover, the result that the restoration accuracy had improved even when which combining with the technique by using the Kalman filter for the Inverse Halftoning so far came out.

• The Journal of the Korea Contents Association
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• v.9 no.11
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• pp.225-230
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• 2009

Filtering has been used to improve the image quality not only in MRI but in most image processing fields. In this paper, modified Fermi-Direc filter was transformed in various shapes, and then the optimum shape was designed. In addition, Newly made filter was applied in real clinic, which showed the obvious improvement in image quality. In conclusion, filtered image was superior to original image in contrast and sharpness. Then, this was proved by the histogram of R, G, B channel used for the quantitative analysis.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.2
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• pp.151-156
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• 2010

This paper is a study on image noise reduction of modified sigma filter by image decomposition using directivity. Conventional sigma filter has been shown to be a good solution both in terms of filtering accuracy and computational complexity. However, the sigma filter does not preserve well small edges especially for high level of additive noise. In this paper, we propose here a new method using a modified sigma filter. In our proposed method the input image is first decomposed in two components that have features of horizontal, vertical and diagonal direction. Then, two components are applied HPF and LPF. By applying a conventional sigma filter separately on each of them, the output image is reconstructed from the filtered components. Added noise is removed and our proposed method preserves the edges from the image. Comparative results from experiments show that the proposed algorithm achieves higher gains, on average, 2.6 dB PSNR than the sigma filter and 0.5 dB PSNR than the modified sigma filter. When relatively high levels of noise added, the proposed algorithm shows better performance than two conventional filters.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.83-86
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• 2019

Histogram equalization is extensively used for image contrast enhancement in various applications due to its effectiveness and its modest functions. In image research, image enhancement is one of the most significant and arduous technique. The image enhancement aim is to improve the visual appearance of an image. Different kinds of images such as satellite images, medical images, aerial images are affected from noise and poor contrast. So it is important to remove the noise and improve the contrast of the image. Therefore, for this purpose, we apply a median filter on MR image as the median filter remove the noise and preserve the edges effectively. After applying median filter on MR image we have used intensity transformation function on the filtered image to increase the contrast of the image. Than applied the histogram equalization (HE) technique on the filtered image. The simple histogram equalization technique over enhances the brightness of the image due to which the important information can be lost. Therefore, adaptive histogram equalization (AHE) and contrast limited histogram equalization (CLAHE) techniques are used to enhance the image without losing any information.

• Journal of radiological science and technology
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• v.24 no.1
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• pp.17-22
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• 2001

Medical X-ray examination are increased double for the last $6{\sim}8$ years. Therefore a patient exposure dose should be decrease half every 7 years. We made an experiment on copper filter thickness to decrease a patient exposure dose up to half and compared to the Image quality by MTF. The results as follow 1. A thin region like extremities needs a thicker Cu filter as compared a thick region. 2. 1/2 reduction filter must be thicker when kVp Increase. 3. Exposure factor should be increas when using 1/2 reduction filter ; extremity is 4.0 times, chest 2.9 times, skull 1.62 times, and abdomen 1.58 times 4. The MTF of using 1/2 reduction filter is lower than without filter. But no difference of visual image. 5. 1/2 reduction filter compared with double speed screen showed almost same image quality.

• The Transactions of the Korea Information Processing Society
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• v.6 no.10
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• pp.2830-2837
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• 1999

Image processing steps are consist of image acquisition, preprocessing, region, segmentation and recognition. But image corrupted commonly by noise reduction methods, many filters were proposed like mean filter, median filter, weighted median filter, Cheikh filter, and Kyu-cheol lee filter as spatial noise reduction filtering. We propose a new edge detection algorithm so that we find out edge existence and nonexistence. In non-edge area, we selectively apply weighted median filter based upon using information of difference value between weighted median filter's value and center pixel's value. As a result, we finally prove a better performance of noise reduction by applying adaptive weighted median filter and improvement of processing time through using simple algorithm.

• 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.