• 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.

• Korean Journal of Digital Imaging in Medicine
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• v.4 no.1
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• pp.166-180
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• 1998

$\cdot$ 영상 압축은 영상의 통계학적 분포, 반복성을 이용하여 빈도가 높은 데이터는 적은 수의 bits를, 빈도가 낮은 데이터에는 보다 많은 수의 bits를 할당하여 전체 영상을 나타내는 bits 수를 줄이는 것임. $\cdot$ 영상 압축은 크게 Lossy Coding, Lossless Coding으로 나뉘며, Lossy coding은 DCT, 양자화기, VLC Codes를 쓰며 압축 율은 높으나 원래의 영상을 정확히 복원하지 못함. $\cdot$ 영상 압축에 대한 국제 규격 협회는 JPEG, MPEG I, MPEG II, MPEG IV, H.261, H.263 등이 있으나 본 seminar에서는 JPEG 규격만 논함. $\cdot$ 의학 영상은 Resolution이 크고 study 단위로 관리되기 때문에 영상 데이터량이 많으나 진단의 목적으로 쓰이기 때문에 주로 lossless 압축을 쓰게 되나 압축율이 낮음.(3:1 이하). 최근에는 Fractal, Wavelet Coding을 통한 압축율을 증가 시키는 Image Compression Algorithms이 활용됨. $\cdot$ MPEG은 동영상의 압축 표준안이며, 동영상은 한frame 당 25개 이상의 정지 화상으로 이루어지기 때문에 JPEG 규격에서 사용되었던 기법이 그대로 활용되며 영상과 영상간, 또는 frame과 frame 간의 여상의 변화, 움직임을 Vector로 coding하는 interframe Coding 기법을 활용하나 설명하기에는 광범위한 topic이므로 본 seminar에서는 생략함.

• Journal of Information Processing Systems
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• v.11 no.4
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• pp.601-615
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• 2015

Region of interest (ROI) is the most informative part of a medical image and mostly has been used as a major part of watermark. Various shapes ROIs selection have been reported in region-based watermarking techniques. In region-based watermarking schemes an image region of non-interest (RONI) is the second important part of the image and is used mostly for watermark encapsulation. In online healthcare systems the ROI wrong selection by missing some important portions of the image to be part of ROI can create problem at the destination. This paper discusses the complete medical image availability in original at destination using the whole image as a watermark for authentication, tamper localization and lossless recovery (WITALLOR). The WITALLOR watermarking scheme ensures the complete image security without of ROI selection at the source point as compared to the other region-based watermarking techniques. The complete image is compressed using the Lempel-Ziv-Welch (LZW) lossless compression technique to get the watermark in reduced number of bits. Bits reduction occurs to a number that can be completely encapsulated into image. The watermark is randomly encapsulated at the least significant bits (LSBs) of the image without caring of the ROI and RONI to keep the image perceptual degradation negligible. After communication, the watermark is retrieved, decompressed and used for authentication of the whole image, tamper detection, localization and lossless recovery. WITALLOR scheme is capable of any number of tampers detection and recovery at any part of the image. The complete authentic image gives the opportunity to conduct an image based analysis of medical problem without restriction to a fixed ROI.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.10
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• pp.2409-2416
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• 2015

This paper presents an orientation-based adaptive prediction method for effective lossless image compression. For a robust prediction, the proposed method estimates the directional information and the property near the current pixel in a support region-based fashion, not a pixel-based one which is sensitive to a small variation. We improve the prediction performance effectively by selection of the prediction pixel adaptively according to the similarity between support regions of the current pixel and the neighboring pixels. Comprehensive experiments demonstrate that the proposed scheme achieves excellent prediction performance measured in entropy of the prediction error compared to a number of conventional prediction methods such as MED, GAP, and EDP. Moreover the complexity of the proposed algorithm measured by average execution time is low compared to MED which is the simplest prediction method.

• Journal of Korea Game Society
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• v.9 no.6
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• pp.171-178
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• 2009

Multiple layer displacement mapping methods are able to represent more complex and general geometries which cannot be presented by single layer displacement mapping methods, and provide a realistic scene to digital contents such as 3D games and movies with relatively low costs. However, as we use more layers for details, data space is wasted more because lower layers have less displacement data than higher layers. In this paper, we suggest a lossless compression and rendering method of a multiple layer displacement map. Since we compress the map without data loss, the proposed method provides the same quality as the rendering result that uses an original multiple layer displacement map.

• Journal of Korea Game Society
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• v.14 no.6
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• pp.59-68
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• 2014

Memory bandwidth requirements of UHD (Ultra High Definition $4096{\times}2160$) game scenes have been much more increasing. This paper presents a lossless DPCM-GR based compression algorithm using CUDA for solving the memory bandwidth problem without sacrificing image quality, which is modified from DDPCM-GR [4] to support bit parallel pipelining. The memory bandwidth efficiency increases because of using the shared memory of CUDA. Various asynchronous transfer configurations which can overlap the kernel execution and data transfer between host and CUDA are implemented with the page-locked host memory. Experimental results show that the maximum 31.3 speedup is obtained according to CPU time. The maximum 30.3% decreases in the computation time among various configurations.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2363-2366
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• 2003

With the increasing use of multimedia technologies, image compression requires higher performance as well as new features such as embedded Tossy to lossless coding, various progressive order, error resilience and region-of-interest coding. In the specific area of still image encoding, a new standard, the JPEG2000, has been currently developed. This paper presents a new compression scheme based on JPEG2000. In the proposed scheme, gray coding is applied to the wavelet coefficient. Since gray coding produces an image whose bit plane is will clustered. The proposed method improves compression efficiency of the JPEG2000.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1999.06a
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• pp.83-88
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• 1999

In this paper, a novel gray-scale lossless image coder combining context-based minimum mean squared error (MMSE) prediction and entropy coding is proposed. To obtain context of prediction, this paper first defines directional difference according to sharpness of edge and gradients of localities of image data. Classification of 4 directional differences forms“geometry context”model which characterizes two-dimensional general image behaviors such as directional edge region, smooth region or texture. Based on this context model, adaptive DPCM prediction coefficients are calculated in MMSE sense and the prediction is performed. The MMSE method on context-by-context basis is more in accord with minimum entropy condition, which is one of the major objectives of the predictive coding. In entropy coding stage, context modeling method also gives useful performance. To reduce the statistical redundancy of the residual image, many contexts are preset to take full advantage of conditional probability in entropy coding and merged into small number of context in efficient way for complexity reduction. The proposed lossless coding scheme slightly outperforms the CALIC, which is the state-of-the-art, in compression ratio.

• 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.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.8
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• pp.1227-1237
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• 1989

In this paper, we propose a lossless progressive image transmission scheme using hierarchical pyramid structure and classified vector quantizer in DCT domain. By adopting DCT to the hierarchical pyramid signals, we can reduce the spatial redundance. Moreover, the DCT coefficients can be encoded efficiently by using classified vector quantizer in DCT domain. The classifier is simply based on the variance of a subblock. Also, the mirror set of training set of images can improve the robustness of codebooks. Progressive image transmission can be achieved through following processes: from top to bottom level of planes in a pyramid, and from high to low AC variance class in a plane. Some simulation results with real images show that the proposed coding scheme yields a good performance at below 0.3 bpp and an excellent result at 0.409 bpp. The proposed coding scheme is well suited for lossless progressive image transmission as well as image data compression.