• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.6
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• pp.709-713
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• 2005

A new algorithm is proposed for the extraction of line segments to construct 3D wire-frame models of building from the high-resolution aerial images. The purpose of this study Is the accurate and effective extraction of line segments, considering the problems such as discordance of lines and blurred edges existing in the conventional methods. Using the edge map extracted from aerial images, chain code tracking of edges was performed. Then, we extract the line segments considering the strength of edges and the direction of them. SUSAN (Smallest Uni-value Segment Assimilating Nucleus) algorithm proposed by Smith was used to extract an edge map. The proposed algorithm consists of 4 steps: removal of the horizontal, vertical and diagonal components of edges to reduce non-candidate point of line segments based on the chain code tracking of the edge map, removal of contiguous points, removal of the same angle points, and the extraction of the start and end points to be line segments. By comparing the proposed algorithm with Boldt algorithm, better results were obtained regarding the extraction of the representative line segments of buildings, having relatively less extraction of unnecessary line segments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.8A
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• pp.725-732
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• 2002

Block-wise MAP (Maximum A posteriori) decoding algorithm for turbo-codes requires less memory than Log-MAP decoding algorithm. The ER (Bit Error Rate) performance of previous block-wise MAP decoding algorithm depend on the block length and training length. To maximize hardware utilization and perform successive decoding, the block length is set to be equal to the training length in previous MAP decoding algorithms. Simulation result on the BER performance shows that the EBR performance can be maintained with shorter blocks when training length is sufficient. This paper proposes an architecture for area efficient block-wise MAP decoder. The proposed architecture employs the decoding schema for reducing memory by using the training length, which in N times larger than block length. To efficiently handle the proposed schema, a pipelined architecture is proposed. Simulation results show that memory usage can be reduced by 30%~45% in the proposed architecture without degrading the BER performance.

• Journal of the Institute of Convergence Signal Processing
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• v.1 no.2
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• pp.105-114
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• 2000

In this paper, we propose a bandwidth-efficient channel coding scheme using the turbo trellis-coded modulation with multiple symbol detection. The turbo code can achieve good bit error rates (BER) at low SNR. That comprises two binary component codes and an interleaver. TCM codes combine modulation and coding by optimizing the euclidean distance between codewords. This can be decoded with the Viterbi or the symbol-by- symbol MAP algorithm. But we present the MAP algorithm with branch metrics of the Euclidean distance of the first phase difference as well as the Lth phase difference. The study shows that the turbo trellis-coded modulation with multiple symbol detection can improve the BER performance at the same SNR.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.3 s.303
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• pp.1-6
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• 2005

In the Markov network which models disparity map with the Markov Random Fields(MRF), the belief propagation algorithm is operated by message passing between nodes corresponding to each pixel. The initial message value is converged by iterations of the algorithm and the algorithm requires many iterations to get converged messages. In this paper, we simplify the algorithm by regarding the objects in the disparity map as combinations of lines with same message valued nodes to reduce iterations of the algorithm.

• Journal of Biomedical Engineering Research
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• v.18 no.4
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• pp.339-348
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• 1997

In this paper, we propose a coding method to improve compression efficiency for MR image. This can be achieved by combining coding scheme and segmentation scheme which removes noisy background region, which is meaningless for diagnosis in the MR image. In segmentation algoritm, we use full-resolution wavelet transform to extract features of regions in image and Kohonen self-organizing map to classify the features. The subsequent wavelet coder encodes only diagnostically significant foreground regions refering to segmentation map. Our proposed algorithm provides about 15% of bit rate reduction when compared with the same coder which is not combined with segmentation scheme. And the proposed scheme shows better reconstructed image quality than JPEG at the same compression ratio.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.07a
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• pp.83-86
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• 2012

본 논문에서는 다양한 변이 추정 방식 중 영역기반(Area-based) 알고리듬과 특정기반(Feature-based) 알고리듬을 결합한 하이브리드(Hybrid) 변이추정 알고리듬을 제안한다. 제안하는 알고리듬은 Features from Accelerated Segment Test(FAST) 코너 점 추출기[2]를 이용하여 좌, 우 영상 각각의 특징 점을 추출한 후, 특징 점들의 정보를 이용한 스테레오 정함을 통해 신뢰도 높은 초기 변이지도(Disparity map)를 생생하게 된다. 그러나 생성된 초기 변이지도는 조밀하지 못하므로, 조밀한 변이 지도를 획득하기 위해 특징점이 추출된 영역에 대해서는 추정된 초기 변이 값을 이웃 픽셀과의 색 유사도를 고려하여 전파시키고 특징 점이 추출되지 않은 영역에 대해서는 이진 윈도우(Binary window)를 활용한 영역기반 변이추정 알고리듬[1]을 이용하여 변이 값을 추정한다. 이를 통해, 제안 알고리듬은 특징 기반 알고리듬에서 발생할 수 있는 보간법 문제를 해결함과 동시에 신뢰도가 높은 초기 변이지도를 사용함으로써, 영역 기반 알고리듬의 정합 오차를 줄여 신뢰도 높은 변이지도를 생생할 수 있다. 실험 결과 추정된 초기 변이지도는 ground truth와 비교 시 약 99%이상의 정확도를 보이며, 특징 점이 추출된 영역에서 기존의 영역기반 알고리듬보다 더 정확한 변이 값이 추정되었음을 확인하였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.5C
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• pp.386-394
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• 2008

For digital holographic video system, it is important to generate digital hologram as fast as possible. This paper proposed a fixed-point method and fast generation method that can calculate the Fresnel hologram using operation of whole-coordinate recursive addition. To compute the digital hologram, 3D object is assumed to be a collection of depth-map point generated using a PC. Our algorithm can compute a phase on a hologram by recursive addition with fixed-point format at a high speed. When we operated this algorithm on a personal computer, we could maximally compute digital hologram about 70% faster than conventional method and about 30% faster than of [3]'s method.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.4
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• pp.97-105
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• 2016

Radiography image detector produces digital images by collecting the charges from the incident x-ray photons and converting it to the voltage signals and then the digital signals. The fixed-pattern noise from the nonuinform amplifier gains in the employed multiple readout circuits. In order to correct the nonuniform gains, a gain-correction technique which is based on the gain map is conventionally used. Since the photon noise remains in the designed gain map, the noise contaminates the gain-corrected images. In this paper, experimental observations are conducted for filtering the remained noise in the gain map, and a filter optimization algorithm is proposed to efficiently remove the noise. For acquired x-ray images from detectors, the filtered gain maps are evaluated and it is shown that optimization algorithm can improve the filtering performance even for relatively strong fixed-pattern noises, which cannot be removed by a simple filter.

• Journal of Broadcast Engineering
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• v.22 no.6
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• pp.702-712
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• 2017

In this paper, we propose an unsharp masking algorithm using Laplacian as a weight map for the signal structure and a gamma transformation algorithm using image mean intensity as a weight map for mean intensity. The conventional weight map based on the patch has a disadvantage in that the brightness in the image is shifted to one side in the signal structure and the mean intensity region. So the detailed information is lost. In this paper, we improved the detail using unsharp masking of patch unit and proposed linearly combined the gamma transformed values using the average brightness values of the global and local images. Through the proposed algorithm, the detail information such as edges are preserved and the subjective image quality is improved by adjusting the brightness of the light. Experiment results show that the proposed algorithm show better performance than conventional algorithm.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.4
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• pp.363-368
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• 2012

The result of the line simplification algorithm varies with the choice of algorithms, the change in tolerance and the selection of target objects. Three of the algorithms used in this study are Sleeve-fitting, Visvalingam-Whyatt, and Bend-simplify. They were applied to the three kinds of objects which were buildings, rivers, and roads with the five degrees of the tolerance. Through this experiments the vector displacement, the areal displacement, and the angular displacement were measured and the qualitative analysis was performed with the trend line of the errors. The experimental results show that errors were differ from tolerance values, and characteristics of line simplification algorithms based on changes of tolerance were understood.