• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.7
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• pp.1518-1523
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• 2012

Due to development of visual media in various industrial sectors, the importance of image processing is increasing. Among the various image processing areas, edge detection is utilized widely for various fields such as object recognition, object segmentation, the medical and other industries. Edge includes the critical factors of images like size, direction and location. Then conventional methods such as Sobel, Prewitt, Roberts and Laplacian are proposed to detect edge. However, edge detection property of these methods is declined when they are applied to the image which corrupted by AWGN(Additive White Gaussian Noise). Therefore, an algorithm using modified weighted filter is proposed in this paper and our method has excellent property on edge detection.

• International Journal of Contents
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• v.2 no.1
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• pp.5-8
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• 2006

This paper describes a new mechanism of detecting object of interest from a noisy image, without using any a-priori knowledge about the target. It employs a parallel set of filters inspired upon biological findings of mammalian vision. In our proposed system, several basic features are extracted directly from original input visual stimuli, and these features are integrated based on their local competitive relations and statistical information. Through integration process, unnecessary features for detecting the target are spontaneously decreased, while useful features are enhanced. Experiments have been performed on a set of computer generated and real images corrupted with noise.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.11A
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• pp.1880-1888
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• 2001

In wireless communication systems, transmission errors degrade the reconstructed image quality severely. Among various techniques which reduce the degradation, the error concealment technique yields good performance without overheads and the modification of the encoder. In this paper, we have proposed the technique for recovering the corrupted motion vector using the edge direction of blocks which surround the corrupted block, when the video information is compressed by H.263 standard. We uses the property that each object in video sequences shows the same motion. For the estimation of edge directions, the first AC coefficients of blocks are used. Extensive simulation results show that the proposed technique yields good performance with a reduced computational complexity.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.2
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• pp.61-70
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• 2011

Virtualization is a technology that uses a logical environment to overcome physical limitations in hardware. As a part of cost savings and green IT policies, there is a tendency in which recent businesses increase the adoption of such virtualization. In particular, regarding the virtualization in desktop, it is one of the most widely used technology at the present time. Because it is able to efficiently use various types of operating systems in a physical computer. A virtual machine image that is a key component of virtualization is difficult to investigate. because the structure of virtual machine image is different from hard disk image. Therefore, we need researches about appropriate investigation procedure and method based on technical understanding of a virtual machine. In this research, we suggest a procedure of investigation on a virtual machine image and a method for a corrupted image of the VMware Workstation that has the largest number of users.

• 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.

• Journal of Korea Multimedia Society
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• v.20 no.10
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• pp.1671-1677
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• 2017

In this paper, we propose a machine learning method for random noise removal in image deblurring. The proposed method uses a logistic regression to select reliable data to use them, and, at the same time, to exclude data, which seem to be corrupted by random noise, in the deblurring process. The proposed method uses commonly available images as training data. Simulation results show an improved performance of the proposed method, as compared with the median filtering based reliable data selection method.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.9
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• pp.1428-1435
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• 1989

In this paper we propose a new algorithm which extracts spatial arrangement information of texture elements in structural textures. In the proposed algorithm, by the use of projection information in several directions obtained from the texture image we can get two directions which determine the texture structure and the parallelogram grid which isolates texture elements. The isolated texture elements are analyzed and used to synthesize texture images. Computer simulation shows that the proposed method can extract proper spatial structure of the texture element even when the texture image is highly corrupted by additive noise.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.3
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• pp.493-503
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• 1987

Performances of some image restoration filters are compared and evaluated on SNR gain and subjective test. Test images used here are the GIRL and PLANT images corrupted by Gaussian, uniform, BSC, and impulse noise, respectively. Experimental results show that the scalar DCT-Wiener filter among them is comparatively superior to others in Gaussian and uniform noise. On the other hand, the median filter is much better than others in BSC and impulse noise.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.898-901
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• 2000

A new 2-D block Kalman filtering method which uses a nonlinear function is presented to generate a more accurate filtered estimate of a range image that has been corrupted by additive noise. Novel 2-D block Kalman filtering method is constructed of the conventional method and nonlinear function which utilizes to control estimation error. We show that novel 2-D Kalman filtering method using a nonlinear function is effective at reducing the additive noise, not distorting shape edges.

• Journal of the Institute of Convergence Signal Processing
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• v.15 no.4
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• pp.135-140
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• 2014

As the digital image devices are widely used, interests in the software- and the hardware-related image processing become higher and the image processing techniques are applied in various fields such as object recognition, object detection, fingerprint recognition, and etc. For the edge detections Sobel, Prewitt, Laplacian, Roberts and Canny detectors are used and these existing methods can excellently detect the edges of the images without noise. However, in the images corrupted by the impulse noise, these methods are insufficent in noise elimination characteristics, showing unsatisfactory edge detection. Therefore in this paper, in order to obtain excellent edge detection characteristics in the corrupted image by the impulse noise, an detection algorithm is porposed, which uses the central pixel of mask divided by four regions along the axis, calculates the estimated mask according to the representing pixel values in each regions, and detects the final edges by applying the estimates mask and the new directional one.