• Electronics and Telecommunications Trends
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• v.19 no.1 s.85
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• pp.33-42
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• 2004

본 고는 가장 최근에 개발된 HDRI 포맷인 OpenEXR 파일 포맷에 대하여 살펴본다. 지금까지 HDRI 포맷으로서 사용되었던 Log Luv TIFF나 Radiance RGBE와 같은 FP 타입의 HDRI 포맷은 압축 방식에 있어서 모두 손실 압축(loss compression)이거나 또는 너무 많은 메모리(32bits FP)를 소비하는 단점이 있었다. 그러나 ILM에 의해서 개발된 EXR 영상 포맷은 16bits FP 데이터 타입에 무손실 압축(lossless compression)을 제공할 뿐만 아니라 유연한 확장성을 제공하고 있기 때문에 앞으로 영상 산업에서의 비주얼 이펙트 표현에 중요한 역할을 할 것으로 기대된다.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.203-204
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• 2007

In this work, we propose a compression algorithm for depth images, which are obtained from multi-view sequences. The proposed algorithm represents a depth image using a 3-D regular triangular mesh and predictively encodes the mesh vertices using a linear prediction scheme. The prediction errors are encoded with a arithmetic coder. Simulation results demonstrate that the proposed algorithm provides better performances than the JPEG2000 lossless coder.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.264-267
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• 2005

COMS (Communication, Ocean, and Meteorological Satellite) will be launch at end of year 2008. For speedy and security communication of COMS, KARl (Korea Aerospace Research Institute) decided encryption and compression design. Encryption design is based on DES (Data Encryption Standard), so that encryption key generation and management are important issues in COMS operation. And Compression is based on loss and lossless JPEG (Joint Photographic Export Group) standard. JPEG is one of generally using compression algorithm in image.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.11
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• pp.225-228
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• 1996

ECG data are used for the diagnostic purposes with many clinical situations, especially heart disease. In this paper, an efficient ECG data compression technique by wavelet transform and high-speed vector quantization on PMS-B algorithm is proposed. In general, ECG data compression techniques are divided into two categories: direct and transform methods. The direct data compression techniques are AZTEC, TP, CORTES, FAN and SAPA algorithms, besides the transform methods include K-L, Fourier, Walsh, and wavelet transforms. In this paper, we applied wavelet analysis to the ECG data. In particular, vector quantization on PMS-B algorithm to the wavelet coefficients in the higher frequency regions, but scalar quantized in the lower frequency regions by PCM. Finally, the quantized indices were compressed by LZW lossless entropy encoder. As the result of simulation, it turns out to get sufficient compression ratio while keeping clinically acceptable PRD.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.129-132
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• 2001

영역 기반의 영상 압축 방법으로 quadtree 분할 압축 방법이 있다[1][2]. 이 방법은 낮은 bpp환경의 손실 압축에서 우수한 압축성능을 나타내지만 무손실이나 혹은 손실이 거의 없는 그레이 영상 압축에는 적당하지 않다. 본 논문에서는 quadtree 분할 압축을 예측자 및 F함수와 함께 사용하여 무손실이면서 우수한 압축성능을 가지는 무손실 압축 방법을 제안한다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.6 s.312
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• pp.97-104
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• 2006

The state-of-the-art H.264/AVC standard was designed for the lossy video coding so that it could not yield the best performance for lossless video coding. In this paper, we propose two efficient intra lossless coding methods by embedding a pixel-wise prediction into the H.264/AVC. One is based on the pixel-wise prediction for the residual signal of the H.264/AVC intra Prediction and the other suggests a newly additional intra prediction mode for the conventional intra prediction. We found that the proposed lossless coding algorithms could achieve approximately $12%{\sim}25%$ more bit saving compared to the H.264/AVC FRExt high profile for several test sequences in terms of a compression ratio.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.4
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• pp.421-429
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• 2018

While IoT device sensing data or financial transaction data is transmitted in real time, huge data traffic is generated in processing it. This huge data can be effectively compressed or transmitted using universal code, which is a real-time lossless compressor. In this paper, we propose our BL-beta code, which is newly developed universal code for compressing stock trading data, which the maximum range of measured values is difficult to predict and is generated within a relatively constant range over a very short period of time. For compressing real-time stock trading data, Compared with the fixed length bit transmission, the compression efficiency is at least 49.5% higher than that of the fixed length bit transmission, and the compression transmission performance is 16.6% better than the Exponential Golomb code.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.7C
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• pp.658-665
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• 2005

Re-assignment scheme of index in index image is called reindexing. It has been well known that index image can be reindexed without losslessness. In this paper, we introduces an adaptive rank based reindexing scheme using co-occurrence frequency between neighboring pixels. Original index image can be converted into rank image by the proposed scheme. Using the proposed scheme, a better compression efficiency can be expected because most of the reindexed values(rank) get distributed with a smaller variance than the original index image. Experinental results show that the proposed scheme achieves a much better compression performance over GIF, arithmetic coding, Zeng's algorithm and RIAC scheme.

• Spatial Information Research
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• v.19 no.1
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• pp.107-116
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• 2011

Due to development of environment of wireless Internet, location based services on the basis of spatial data have been increased such as real time traffic information as well as CNS(Car Navigation System) to provide mobile user with route guidance to the destination. However, the current application adopting the file-based system has limitation of managing and storing the huge amount of spatial data. In order to supplement this challenge, research which is capable of managing large amounts of spatial data based on embedded database system is surely demanded. For this reason, this study aims to suggest the lossless compression technique by using the hybrid approach of BytePacking and Lempel-Ziv which can be applicable in DBMS so as to save a mass spatial data efficiently. We apply the proposed compression technique to actual the Seoul and Inchcon metropolitan area and compared the existing method with suggested one using the same data through analyzing the query processing duration until the reconstruction. As a result of comparison, we have come to the conclusion that suggested technique is far more performance on spatial data demanding high location accuracy than the previous techniques.

• The Transactions of the Korea Information Processing Society
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• v.5 no.10
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• pp.2704-2712
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• 1998

In this paper, a MRI image compression technique, which allocates bits effectively by using lossless coding for region having important infommtion to decide disease and lossy coding for the rest, is proposed. In the proposed method, for MHI images needed to rccognize disk disease, we recognizc region having important objects by using the characteristics of c1isease. As the recognized region is imrxlrtant to decide whether disease exists or not, it is compressed by lossless coding and the rest is compressed by lossy coding, Also for the region compressed by lossy coding, we can obtain fine reconstructed images without blocking effect by adopting fractal coding in wavelet transform domain.