• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.504-506
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• 1993

The Joint Photographic Experts Group (JPEG) standard was proposed by the International Standardization Organization (ISO/SC 29/WG 10) and the CCITT SG VIII as an international standard for digital continuous-tone still image compression. The JPEG standard has been widely accepted in electronic imaging, computer graphics, and multi-media applications, however, due to the lossy character of the JPEG compression its application in the field of medical imaging has been limited. In this paper, the JPEG standard was applied to a series of head sections of magnetic resonance (MR) images (256 gray levels, $256{\times}256$ size) and its performance was investigated. For this purpose, DCT-based sequential mode of the JPEG standard was implemented using the CL550 compression chip and progressive and lossless coding was implemented by software without additional hardware. From the experiment, it appears that the compression ratio of about 10 to 20 was obtained for the MR images without noticeable distortion. It is also noted that the error signal between the reconstructed image by the JPEG and the original image was nearly random noise without causing any special-pattern-related artifact. Although the coding efficiency of the progressive and hierarchical coding is identical to that of the sequential coding in compression ratio and SNR, it has useful features In fast search of patient Image from huge image data base and in remote diagnosis through slow public communication channel.

• Proceedings of the KOSOMBE Conference
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• v.1995 no.11
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• pp.113-116
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• 1995

Medical image compression using the wavelet transform has been tried. Due to the flexibility in representing nonstationary image signal in both time and frequency domains and its ability to adapt human visual characteristics, wavelet transform has unique advantage in images compression. In the proposed wavelet compression original image is decomposed into multi-scale bands. Different scale factors are employed in the quantization of wavelet decomposed images in different bands. For the lowest band, a predictor is designed and error signal is entropy coded. For high scale bands, runlength coding for toro run is used with Huffman coding. From simulation with magnetic resonance images($256\times256$ size, 256 graylevels) the proposed algorithm is superior to the JPEG by more than 2.5 dB in near lossless compression (CR = 8 - 10).

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.921-922
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• 2008

In this paper, we propose a lossless compression algorithm using adaptive DPCM(Differential Pulse Coded Modulation) for enhancing the compression ratio. To improve the compression efficiency, various DPCM modification algorithms have been proposed. Proposed algorithm presents 16 DPCM methods and adaptively selects the DPCM method for each block. The experimental results show that proposed DPCM algorithm has better performance on compression ratio than JPEG standard.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.9B
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• pp.1259-1266
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• 2001

최근에 텍스트 압축에 뛰어난 성능을 가지는 블록 정렬 알고리즘인 BW변환 (Burrows-Wheeler Transform)이 소개되었다. 그러나 영상 압축에 BW변환을 직접 적용하면 영상과 텍스트가 갖는 상관성이 서로 다르기 때문에 만족할 만한 압축효과를 기대할 수 없게 된다. 따라서 본 논문에서는 가역의 L-SSKF(Lossless Symmetric Short Kernel Filter)를 사용한 계층적 대역분할로 영상화소 사이의 상관성을 줄인 후 BW변환을 하는 방법과 GAP(Gradient Adjusted Prediction)를 사용하여 LL 대역에 많이 분포된 상관성을 줄인 후 BW변환을 하는 방법을 제안한다. 실험결과 제안한 방법이 기존의 무손실 JPEG 표준안과 LZ 기반의 압축방법(PKZIP) 등에 비해 압축성능이 개선됨을 확인할 수 있었다.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2727-2729
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• 2002

In an emergency telemedicine system such as High-quality Multimedia based Real-time Emergency Telemedicine(HMRET) service, it is very important to examine the status of the patient continuously using the multimedia data including the biological signals(ECG, BP, Respiration, $SpO_2$) of the patient. In order to transmit these data real time through the communication means which have the limited transmission capacity. It is also necessary to compress the biological data besides other multimedia data. For the HMRET service, we developed the lossless biological signal compression program in MSVC++ 6.0 using DPCM method and JPEG Huffman table, and tested in an internet environment.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2002.06a
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• pp.200-208
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• 2002

As the computer communication becomes generalized thanks to the advancement in information technology the technology to process a large amount of images is much rare required. This paper proposed lossless image compression method using quadtree algorithm and F-transform, which efficiency transmission and storage. The computer simulation shows that Compression ratio to make use of proposed method turned out to be improved more significantly compared with the established L-JPEG, LOCO-I, CALIC.

• Journal of Advanced Navigation Technology
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• v.19 no.6
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• pp.614-622
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• 2015

Binary MQ arithmetic coding is widely used recently as a basic entropy coder in multimedia coding system. MQ coder esteems high in compression efficiency to be used in JBIG2 and JPEG2000. The importance of arithmetic coding is increasing after it is adopted as an unique entropy coder in HEVC standard. In the binary MQ coder, arithmetic approximation without multiplication is used in the process of recursive subdivision of range interval. Because of the MPS/LPS exchange activity happened in MQ coder, output byte tends to increase. This paper proposes an enhanced binary MQ arithmetic coder to make use of a lookup table for AQe using quantization skill in order to reduce the deficiency. Experimental results show that about 4% improvement of compression in case of JBIG2 for bi-level image compression standard. And also, about 1% improvement of compression ratio is obtained in case of lossless JPEG2000 coding. For the lossy JPEG2000 coding, about 1% improvement of PSNR at the same compression ratio. Additionally, computational complexity is not increasing.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.185-188
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• 2002

With improved network system and development of computer technology, a lot of hospitals are equipping PACS that deals with process and transmission of the medical images. Owing to equipment of PACS the problems on transmission and storage of the medical images were treated. The way to solve the problems is to use various image processing techniques and compression methods This paper describes RLC in lossless image compression method, JPEG using DCT in loss image compression applied to medical images as way implementing DICOM standard. Now the medical images were compressed with Wavelet transform method have been taken advantage of image process. And compression rate of each compression methods was analyzed.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.1C
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• pp.35-43
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• 2005

This paper introduces a new algorithm to improve compression performance of 256 color images called palette-based or indexed images. The proposed scheme counts each frequency of index values after present index value and determines each rank for every index value by sorting them in descending order. Then, the scheme makes ranked index image instead of original indexed image using the way to replace index values with ranks. In the ranked index image's distribution produced as a result of this algorithm, the higher ranked index value, the more present same values. Therefore, data redundancy will be raised and more efficient performance of compression can be expected. Simulation results verify that because of higher compression ratio by up to 22.5, this newly designed algorithm shows a much better performance of compression in comparison with the arithmetic coding, intensity-based JPEG-LS and palette-based GIF.