• Proceedings of the KOSOMBE Conference
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• v.1996 no.11
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• pp.293-296
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• 1996

In this paper, we studied two image characteristics, similarity and smoothness, which give rise to local and global redundancy in image representation. The similarty means that any patterns in the image repeat itself anywhere in the rest of image. The smoothness means that the gray level values within a given block vary gradually rather than abruptly. In this sense, we propose a lossless medical image compression scheme which exploits both types of redundancy. This method segments the image into variable size blocks and encodes them depending on characteristics of the block. The proposed compression schemes works better than other compression schemes such as the huffman, the arithmetic, the Lempel-Ziv and the lossless scheme of JPEG.

• Journal of Biomedical Engineering Research
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• v.15 no.4
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• pp.475-480
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• 1994

For the effective management of medical images, it becomes popular to use computing machines in medical practice, namely PACS. However, the amount of image data is so large that there is a lack of storage space. We usually use data compression techniques to save storage, but the process speed of machines is not fast enough to meet surgical requirement. So a special hardware system processing medical images faster is more important than ever. To meet the demand for high speed image processing, especially image compression and decompression, we designed and implemented the medical image CODEC (COder/DECoder) based on MISD (Multiple Instruction Single Data stream) architecture to adopt parallelism in it. Considering not being a standard scheme of medical image compression/decompression, the CODEC is designed programable and general. In this paper, we use JPEG (Joint Photographic Experts Group) algorithm to process images and evalutate the CODEC.

• 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).

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.181.2-181
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• 2001

Stereo PACS (Picture Archiving and Communication System) is not available yet because of some limitations of medical stereo image software and viewing devices. As a stereo PACS viewer, we designed two functions. One is selecting and viewing a multiplexed stereo image directly, and the other is selecting a stereo pair image (left and right sides both) and merging the stereo pair image into a multiplexed image in software. For the medical image compression of 3-D stereo endoscopic images, we used JPEG and Wavelet compression and to determine an acceptable compression rate using PSNR (Peak Signal-to-Noise Ratio). As a result, we got the conclusion that medically acceptable image compression rate should have the PSNR of above about 40[dB] (JPEG (5:1), Wavelet (10:1)).

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.6
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• pp.453-456
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• 2004

Due to the bandwidth and storage limitations medical images are needed to be compressed before transmission and storage. DICOM (Digital Imaging and Communications in Medicine) specification, which is the medical images standard, provides a mechanism for supporting the use of JPEG still image compression standard. In this paper, we explain a method for compressing medical images by PEG standard and propose two methods for JPEG compression. First, because medical images differ from natural images in optical feature, we propose a method to design adaptively the quantization table using spectrum analysis. Second, because medical images have higher pixel depth than natural images do, we propose a method to design Huffman table which considers the probability distribution feature of symbols. Simulation results show the improved performance compared to the quantization table and the adjusted Huffman table of JPEG standard.

• Journal of Biomedical Engineering Research
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• v.10 no.2
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• pp.173-178
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• 1989

A vector quantization technique using a variable block size was applied to image compression of digitized X -ray films. Whether the size of VQ block should be subdivided or not is determined experimentally by the threshold value. The simulation result shows that the performance of the proposed vector quantizer is suitable for the medical image coding, which is applicable to PACS( Picture Archiving and Communication System).

• Proceedings of the KOSOMBE Conference
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• v.1992 no.05
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• pp.58-63
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• 1992

The discrete cosine transform (DCT)-based progressive coding standard proposed by the International Standardization Orgnnization (ISO) Joint Photographic Experts Groups (JPEG) is investigated for medical image compression and the performance of the JPEG is compared to that of the full-frame bit-allocation (FFBA) technique. From the comparison, the JPEG standard appeals superior to the FFBA technique in the following aspects: 1) JPEG achieves higher compression than the FFBA technique with less mean square error. 2) Less Gibb's artifact is observed in the compressed images by the JPEG. 3) Computational time for the JPEG is about one-fourth or the FFBA technique. Other attractive points of the JPEG include: Implementation of the JPEG with VLSIs is commercially available in relative low price and the JPEG compression format can easily be interchangeable with other applications.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.5
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• pp.14-22
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• 2007

PACS is an integrated communication network system which is consists of image acquisition devices, storage archiving units, display stations, computer processors, and database management systems. In medical industry, they have been introduced the medical equipments through PACS systems based on the DICOM standard. In this paper, we have reviewed the visual quality performance of various JPEG and JPEG2000 compression options for medical images. Through the realized the transmission mode on DICOM standard, the developed DICOM viewer has been shown in medical applications.

• Proceedings of the KOSOMBE Conference
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• v.1993 no.05
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• pp.38-41
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• 1993

For efficient transmission and storage of digital images, the requirements of image compression is incresing. Because the medical images contain diagnostic information small distortion has been more important factor than the low rate in such images. Generally the distortion in image is the difference of pixel values. However the image is percieved by human visual systems. So it is reasonable that human visual system characteristics be used as criteria of the image compression. In this paper, the Just Noticeable Difference curve is used as criteria of determining the homogeniety of a block and acceptibility of distortions. And Block Truncation Coding using spatial masking effect of eyes is adopted to code the blocks which contain line components. And small blocks which varies slowly can be approximated to polynomial functions successfully. We proposed the hybrid block coding scheme based on the block characteristics and human visual system characteristics. Simulation to several kinds of the medical images using this method showed that medical images can be compressed 5:1 - 10:1 without noticeable distortion.

• Journal of Broadcast Engineering
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• v.9 no.3
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• pp.246-256
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• 2004

In this paper, we proposed a new lossless image compression algorithm. Lossless image compression has been used in the field that requires the accuracy and precision. Thus, application areas using medical unaging, prepress unaging, image archival systems, precious artworks to be preserved, and remotely sensed images require lossless compression. The compression ratio from lossless image compression has not been satisfactory, thus far. So, new method of lossless image compression has been investigated to get better compression efficiency. We have compared the compression results with the most typical compression methods such as CALIC and JPEG-LS. CALIC has shown the best compression-ratio among the existing lossless coding methods at the cost of the extensive complexity by three pass algorithm. On the other hand, JPEG-LS's compression-ratio is not higher than CALIC, but was adopted as an international standard of ISO because of the low complexity and fast coding process. In the proposed method, we adopted an adaptive predictor that can exploit the characteristics of individual images, and an adaptive arithmetic coding with multiple probability models. As a result, the proposed algorithm showed 5％ improvement in compression efficiency in comparison with JPEG-LS and showed comparable compression ratio with CALIC.