• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.11
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• pp.1103-1116
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• 1991

The characteristics of transform coefficients of discrete Gabor transform and the performances of their progressive coding are investiganted. The adaptive transform coding SAC is used for the progressive transmission. Exprerimental results show that although DGT has relatively low energy compaction property and coding efficiency, it yields good quality with greaty reduced block artifact and good edge at each stage of the progressive transmission.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.11
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• pp.2375-2380
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• 1997

The need for developing effective coding techniques for various multimedia services is increasing in order to meet the demand for image data. In this paper, a zeroblock coding algorithm is proposed for progressive transmission of images. The zeroblock coding algorithm is constructed as an embedded coding so that the encoding and decoding process can be terminated at any point and allowing reasonable image quality. Some features of zeroblock coding algorithm are 1) coding of subband images by prediction of the insignificance of blocks across subband leels, 2) aset of sate transition rules for representing the significance map of blocks, and 3) block coding by vector quantization using a multiband codebook consisting of several subcodebooks dedicated for each subband at a given threshold.

• Journal of Biomedical Engineering Research
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• v.18 no.4
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• pp.349-356
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• 1997

In this paper, we propose the lossless coding: scheme for progressive transmission of medical images. The input image is decomposed by the proposed fast adaptive subband decomposition method which is suited for a lossless coding. The decomposed images are coded by an arithmetic coder with two conditioning pixels, and the conditioning pixels are selected differently according to the property of the subbands. The conditioning contexts are usually quantized to reduce the conditional state, and the optimization method of quantization is proposed For the purpose of improving compression ratio in this paper. The proposed lossless coding scheme provides the asymmetric structure of cosec and results in better compression ability than the JPEC lossless coding[ 1 ].

• Proceedings of the KOSOMBE Conference
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• v.1991 no.11
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• pp.48-53
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• 1991

The discrete cosine transform (DCT)-based progressive and hierarchical coding schemes developed by the International Standardization Organization (ISO) Joint Photographic Experts Groups (JPEG) are implemented and evaluated for the application of medical image communication. For a series of head sections of magnetic resonance images, a compression ratio of about 10 is obtained by the algorithm without noticeable image degradation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.5
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• pp.685-694
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• 1993

A progressive image transmission (PIT) scheme based on the classified transform vector quantization (CVQ) technique using the lapped orthogonal transform (LOT) and human visual system (HVS) weighting is proposed in this paper. Conventional block transform coding of images using DCT produces in general undesirable block-artifacts at low bit rates. In this paper, image blocks are transformed using the LOT and classified into four classes based on their structural properties and further divided adaptively into subvectors depending on the LOT coefficient statistics with HVS weighting to improve the reconstructed image quality by adaptive bit allocation. The subvectors are vector quantized and transmitted progressively. Coding tests using computer simulations show that the LOT/CVQ based PIT of images is a effective coding scheme. The results are also compared with those obtained using PIT/DCTVQ. The LOT/CVQ based PIT reduces the block-artifacts significantly.

• Proceedings of the KOSOMBE Conference
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• v.1994 no.12
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• pp.31-38
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• 1994

This paper proposed signal decomposition and multiresolution representation through wavelet transform using wavelet orthonormal basis. And it suggested most appropriate filter for scaling function in multiresoltion representation and compared two compression method, arithmetic coding and Huffman coding. Results are as follows 1. Daub18 coefficient is most appropriate in computing time, energy compaction, image quality. 2. In case of image browsing that should be small in size and good for recognition, it is reasonable to decompose to 3 scale using pyramidal algorithm. 3. For the case of progressive transmittion where requires most grateful image reconstruction from least number of sampls or reconstruction at any target rate, I embedded the data in order of significance after scaling to 5 step. 4. Medical images such as information loss is fatal have to be compressed by lossless method. As a result from compressing 5 scaled data through arithmetic coding and Huffman coding, I obtained that arithmetic coding is better than huffman coding in processing time and compression ratio. And in case of arithmetic coding I could compress to 38% to original image data.

• 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 IEEK Conference
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• 2001.06c
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• pp.73-76
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• 2001

We propose a new method for image coding that it is based on highly related property between a spatial image and wavelet transform image. The characteristics have an important role in the design of proposed algorithm. This algorithm for image coding is to obtain high compression rate at low bit rate. The other side, the high activity regions are related to significant coefficients which give much influence to image reconstruction, because they mean the important factor to represent the appearance of images such as edge or boundary. For some images with low activity, we can obtain the reconstructed image with near to 30 dB at 150: 1 compression ratio.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.1
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• pp.111-119
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• 1994

In this paper we propose a reversible image coding methods with progressive build-up function by bit-plane of multi-lavel image. Firstly, the differencial conversion is applied to reduce the entropy of source images. Then the bit-plane sequences of converted images are coded by means of the newly designed VFRL(Variable to Fixed Run-Llength) code and the RDHC(Run-length Dynamic Huffman Coding). We aim to the simple construction to reduce the complexity. The computer simulated results show that the proposed methods are very effective to the multi-level digital images. For "GIRL" and "COUPLE" of 1EEE monochromatic standard images, the compressibility are superior to the results obtained by the well-known universal codes.own universal codes.

• Journal of the Korea Computer Graphics Society
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• v.17 no.2
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• pp.17-26
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• 2011

This paper presents an interactive progressive image transmission method, which enables a remote user to interactively select and transmit preferred regions from an index image. Our enhanced quadtree decomposition using PSNR-based rules and new implicit quadtree coding provide better rate-distortion performance than previous quadtree coders as well as leading bit plane methods. An adaptive traversal of child nodes is introduced for better visual display of restored images. Depth-first traversal combined with breadth-first traversal of the quadtree to accomplish interactive transmission as presented, results in a method that provides competitive performance at a low level of computational complexity. Moreover, our decoding requires only simple arithmetic which is enabling our method to be used for real-time mobile applications.