• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1998.06a
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• pp.33-36
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• 1998

Most image restoration problems are ill-posed and need to e regularized. A difficult task in image regularization is to avoid smoothing of image edges. In this paper, were proposed an edge-preserving image restoration algorithm using block-based edge classification. In order to exploit the local image characteristics, we classify image blocks into edge and no-edge blocks. We then apply an adaptive constrained least squares (CLS) algorithm to eliminate noise around the edges. Experimental results demonstrate that the proposed algorithm can preserve image edges during the regularization process.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.167-170
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• 2000

In this paper, we propose the edge compensation algorithm which connects the adjacent edges without losing the information of the skeletons on the edge image. The proposed edge compensation algorithm is composed of succeeding two steps. In the first step, the uplifted image is obtained by applying the uplifting process to the edge image. The next step is to extract the edge image from the uplifted image using the skeleton extraction algorithm. Experimental results show that the proposed method connects the adjacent edges without the distortion of the original edge information compared to the traditional method

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.2
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• pp.162-171
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• 1991

This paper presents an algorithm for compressing image data by separating the image into two parts. I.e. edge image containing high-frequency components and non-edge image containing low-frequency components of image. The edge image is extracted by using 8 level compass gradient masks and the non-edge image is obtained by removing the edge image from the original image. The edge image is coded by Huffman run-length code and the non edge image is transformed first by DCT and the transformed images is coded next by a quantized bit allocation table. For an example image. GIRL. the proposed algorithm shows bit rate of 0.52 bpp with PSNR of 36dB.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1268-1271
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• 2003

In the edge detection of RS image, the useful detail losing and the spurious edge often appear. To solve the problem, we use the dyadic wavelet to detect the edge of surface features by combining the edge detecting with the multi-resolution analyzing of the wavelet transform. Via the dyadic wavelet decomposing, we obtain the RS image of a certain appropriate scale, and figure out the edge data of the plane and the upright directions respectively, then work out the grads vector module of the surface features, at last by tracing them we get the edge data of the object therefore build the RS image which obtains the checked edge. This method can depress the effect of noise and examine exactly the edge data of the object by rule and line. With an experiment of a RS image which obtains an airport, we certificate the feasibility of the application of dyadic wavelet in the object edge detection.

• Journal of Korea Multimedia Society
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• v.19 no.6
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• pp.990-1002
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• 2016

In this paper, we propose a new compression method for the edge image by analyzing the characteristics and the distribution of pixel values of the edge image. The pixel values of the edge image have the Gaussian distribution around '0', and most of the pixel values are `0`. By these analyses we suggest the Zero-Based codec that expresses all values in a CU by a single bit flag. Also, in order to reduce the computational complexity of the proposed codec, the block partition and the intra-prediction techniques are proposed by using edge information like the number of each edge direction, the distribution and the amplitude of a major edge direction in the CU. Experimental results show that the proposed codec leads to a slighter distortion in Y domain than that of HEVC, but has far faster processing speed up to 53 times while it maintains the similar image quality compared to HEVC.

• Journal of the Korea Society of Computer and Information
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• v.9 no.2
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• pp.49-56
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• 2004

In this paper, we design edge class that can processed digital image effectively, edge is a important information including the point of shape information for a object detection or recognition in the digital image. Therefore, it is of very importance, which managed effectively the edge and can use a variety availability in digital image Processing, after edge detection. The environment using the existing digital image processing system has limits of use and speed. In this paper, we design edge class that can managed detected edges and it analyzes existing methods by edge detection algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.450-470
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• 2023

Traditional cloud computing faces some challenges such as huge energy consumption, network delay and single point of failure. Edge computing is a typical distributed processing platform which includes multiple edge servers closer to the users, thus is more robust and can provide real-time computing services. Although outsourcing data to edge servers can bring great convenience, it also brings serious security threats. In order to provide image retrieval while ensuring users' data privacy, a privacy preserving image retrieval scheme in edge environment is proposed. Considering the distributed characteristics of edge computing environment and the requirement for lightweight computing, we present a privacy-preserving image retrieval scheme in edge computing environment, which two or more "honest but curious" servers retrieve the image quickly and accurately without divulging the image content. Compared with other traditional schemes, the scheme consumes less computing resources and has higher computing efficiency, which is more suitable for resource-constrained edge computing environment. Experimental results show the algorithm has high security, retrieval accuracy and efficiency.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.1121-1124
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• 2005

Edge Histogram Descriptor는 image의 edge 분포 정보를 표현하며 방향성을 가지는 Bio Image 검색에 있어 높은 검색 성능을 나타낸다. 그러나 Bio Image의 객체 분포의 특성으로 인해 지역적 edge 분포 비교는 충분한 검색 성능을 보장하지는 못한다. 본 논문에서는 특징 block을 이용한 효율적인 검색 알고리즘을 제안한다. Local histogram으로부터 Global bin을 얻어 image의 대표 방향성을 선정하고 특징 block을 선정한다. 특징 block의 비교는 edge 분포와 함께 주요 객체의 위치 정보를 더하는 효과를 가진다. Bio Image의 검색 실험에서 제안 알고리즘은 향상된 검색 성능을 보여준다. 또한 Bio image 검색을 위한 descriptor 조합 연구에도 적용 가능하여 검색 효율을 기대할 수 있다.

• Journal of the Semiconductor & Display Technology
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• v.15 no.3
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• pp.51-56
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• 2016

This paper proposes a new image enhancement method for an infrared thermal image. The proposed method uses both Laplacian and Prewitt edge detectors. Without a visible light, it uses an infrared image for the edge detection. The method subtracts contour images from the infrared thermal image. It results black contours of objects in the infrared thermal image. That makes the objects in the infrared thermal image distinguished clearly. The proposed method is implemented using C language in an embedded Linux system for a high-speed real-time image processing. Experiments were conducted by using various infrared thermal images. The results show that the proposed method is successful for image enhancement of an infrared thermal image.

• The KIPS Transactions:PartB
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• v.9B no.5
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• pp.579-586
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• 2002

The edge descriptor proposed by MPEG-7 standard is a representative approach for the contents-based image retrieval using the edge information. In the edge descriptor, the edge information is the edge histogram derived from a gray-level value image. This paper proposes a new method which extracts color edge information from color images and a new approach for the contents-based image retrieval based on the color edge histogram. The poposed method and technique are applied to image retrieval of the e-catalogue. For the evaluation, the results of image retrieval using the proposed approach are compared with those of image retrieval using the edge descriptor by MPEG-7 and the statistics shows the efficiency of the proposed method. The proposed color edge model is made by combining the R,G,B channel components vectorially and by characterizing the vector norm of the edge map. The color edge histogram using the direction of the color edge model is subsequently used for the contents-based image retrieval.