• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.4
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• pp.38-38
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• 2001

본 논문에서는 웨이브릿 영역에서의 영역 분류와 대역간 예측 및 선택적 벡터 양자화를 이용한 다분광 화상테이타 압축 기법을 제안하였다. 이 방법에서는 각 대역을 웨이브릿 변환 후, 각 대역의 기저밴드의 대역별 특성을 이용하여 영역 분류를 행하였다. 그리고, 다른 대역과 해상도가 동일하고 공간적 분산이 작으며 분광적 상관성이 큰 기준대역 (reference channel)을 결정한 뒤, 이를 영역별 스칼라 및 분류별 가변 벡터 양자화를 행하여 부호화 하였다. 또한 기준대역과의 대역간 상관성이 큰 대역들에 대해서는 영역별 대역간 예측을 행한 후, 활동도가 높은 블록에 대해서만 선택적 벡터 양자화로 부호화를 행하였다. 이때, 활동도가 높은 블록들의 위치정보는 기준대역으로부터 얻어지는 임계치 지도 (threshold map; THMAP)를 이용하였다. 즉, 제안한 방법에서는 각 대역에 대해 웨이브릿 영역에서의 영역 분류 후 영역별 대역간 예측을 행함으로써 다분광 화상데이타에 존재하는 대역간 중복성을 제거하고 선택적 벡터 양자화를 행함으로써 대역내 중복성을 효과적으로 제거하여 압축효율을 향상시킨다. 실제 원격 센싱된 인공위성 화상데이타에 대한 실험을 통하여 제안한 기법의 부호화 효율이 기존의 기법에 비하여 우수함을 확인하였다.

• Proceedings of the Korea Contents Association Conference
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• 2005.11a
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• pp.490-494
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• 2005

Multispectral image is wavelet trans formed and classified into one of three classes considering reference characteristics of the subband with the lowest resolution. Recently, aegis of authentitation and creator's copyright has become a matter of great concern by the diffusion of multimedia technique and the growth of the internet and the easily duplicated property of digital data. Consequently, many active researches have been made to protect copyright and to assure integrity by inserting watermark into the digital data. In this paper, watermark is repeated through the entire image and adapted to the content of the image.

• Journal of KIISE:Computer Systems and Theory
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• v.26 no.11
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• pp.1285-1295
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• 1999

본 논문은 방대한 크기의 볼륨 데이타를 효율적으로 렌더링하기 위한 셀 기반 웨이브릿 압축 방법을 제시한다. 이 방법은 볼륨을 작은 크기의 셀로 나누고, 셀 단위로 웨이브릿 변환을 한 다음 복원 순서에 따른 런-길이(run-length) 인코딩을 수행하여 높은 압축율과 빠른 복원을 제공한다. 또한 최근 복원 정보를 캐쉬 자료 구조에 효율적으로 저장하여 복원 시간을 단축시키고, 에러 임계치의 정규화로 비정규화된 웨이브릿 압축보다 빠른 속도로 정규화된 압축과 같은 고화질의 이미지를 생성하였다. 본 연구의 성능을 평가하기 위하여 {{}} 해상도의 볼륨 데이타를 압축하여 쉬어-？ 분해(shear-warp factorization) 알고리즘에 적용한 결과, 손상이 거의 없는 상태로 약 27:1의 압축율이 얻어졌고, 약 3초의 렌더링 시간이 걸렸다.Abstract This paper presents an efficient cell-based wavelet compression method of large volume data. Volume data is divided into individual cell of {{}} voxels, and then wavelet transform is applied to each cell. The transformed cell is run-length encoded according to the reconstruction order resulting in a fairly good compression ratio and fast reconstruction. A cache structure is used to speed up the process of reconstruction and a threshold normalization scheme is presented to produce a higher quality rendered image. We have combined our compression method with shear-warp factorization, which is an accelerated volume rendering algorithm. Experimental results show the space requirement to be about 27:1 and the rendering time to be about 3 seconds for {{}} data sets while preserving the quality of an image as like as using original data.

• The Transactions of the Korea Information Processing Society
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• v.4 no.10
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• pp.2629-2639
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• 1997

The video coding for very low bit-rate has recently received considerable attention, but the conventional coding schemes with block based transform suffer from the blocky effect for the constraints of limited bit-rate. In this paper, we present a video coding system based on wavelet transform and multiresolution motion estimation/compensation for very low bit-rate video. The proposed scheme uses the wavelet transform which is flexible to represent non-stationary image signals and adaptable to the human visual characteristics. The wavelet transformed coefficients are coded by various coding modes in accordance with the sum of absolute error after motion estimation/compensation in wavelet decomposed domain. And simple buffer control technique is applied to handle constant image quality. It is shown that the presented scheme has more acceptable image quality without blocky effects than conventional block based transform video coding.

• The KIPS Transactions:PartB
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• v.10B no.4
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• pp.419-428
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• 2003

Recently, digital watermarking has been proposed as a viable solution to the need of copyright protection and authentication of multimedia data. A robust wavelet-based watermark casting scheme and a watermark retrieval technique are suggested in this paper. We present a method which can add the watermark to the significant coefficients in the DWT domain, and does not require the original image in the detection process. In adaptive watermark casting method is developed to select perceptually significant coefficients for each subband using multiple threshold. In the proposed method, an adaptive multiple threshold scheme is used to reflect characteristics of each subband and complexity of image. The watermark is adaptively weighted in different subbands to achieve robustness as well as high perceptual quality. The watermark, Gaussian random sequence is added to the large coefficients but not in the lowest subband in the DWT domain. Experimental results show that the proposed algorithm produced visually very good watermarked image which has good invisibility to human eyes and very robust against various image processing and compression attacks.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.4
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• pp.567-574
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• 2006

This paper focuses on lossy medical image compression methods for medical images that operate on three-dimensional(3-D) irreversible integer wavelet transform. We offer an application of unbalanced tree structure algorithm to medical images, using a 3-D unbalanced wavelet decomposition and a 3-D unbalanced spatial dependence tree. The wavelet decomposition is accomplished with integer wavelet filters implemented with the lifting method. We have tested our encoder on volumetric medical images using different integer filters and 16 coding unit size. The coding unit sizes of 16 slices save considerable dynamic memory(RAM) and coding delay from full sequence coding units used in previous works. If we allow the formation of trees of different lengths, then we can accomodate more transaxial scales than three. Then the encoder and decoder can then keep track of the length of the tree in which each pixel resides through the sequence of decompositions. Results show that, even with these small coding units, our algorithm with I(5,3)filter performs as well and better in lossy coding than previous coding systems using 3-D integer unbalanced wavelet transforms on volumetric medical images.

• The Journal of the Korea Contents Association
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• v.4 no.1
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• pp.18-23
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• 2004

In this paper, we propose a new visual feature extraction method for content-based image retrieval(CBIR) based on wavelet transform which has both spatial-frequency characteristic and multi-resolution characteristic. We extract visual features for each frequency band in wavelet transformation and use them to CBIR. The lowest frequency band involves spacial information of original image. We extract L feature vectors using fuzzy homogeneity in the wavelet domain, which consider both the wavelet coefficients and the spacial information of each coefficient. Also, we extract 3 feature vectors wing the energy values of high frequency bands, and store those to image database. As a query, we retrieve the most similar image from image database according to the 10 largest homograms(normalized fuzzy homogeneity vectors) and 3 energy values. Simulation results show that the proposed method has good accuracy in image retrieval using 90 texture images.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.4
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• pp.335-343
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• 2001

The conventional wavelet-based fractal image coding has the disadvantage that the encoding takes a long time, since each range block finds the best domain in the image. In this Paper, we propose wavelet-based fractal image coding using SAS(Self Affine System) method and multi-scale factor. It consists of the range and domain blocks in DWT(discrete wavelet transform) region. Using SAS method, the proposed method is that the searching process of the domain block is not required, and the range block selects the domain which is relatively located the same position in the upper level. The proposed method can perform a fast encoding by reducing the computational complexity in the encoding process. In order to improve the disadvantage of SAS method which is reduced image qualify, the proposed method is improved image qualify using the different scale factors for each level. As a result, there is not influence on an image quality, the proposed method is enhanced the encoding time and compression ratio, and it is able to the progressive transmission.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.6
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• pp.32-40
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• 2000

In this paper, we proposed a wavelet-based digital watermarking algorithm using human visual system and subband-adaptive threshold. After the original image is transformed by discrete wavelet transform, the perceptually significant coefficients of the each subband excluding the lowest level subbands are utilized to embed the watermark. To select perceptually significant coefficients for each subband, we use subband-adaptive threshold. For the selected coefficients in the high frequency subbands, the watermark is embedded using HVS. For those of the baseband, the watermark is embedded by conventional embedding method. We tested the performance of the proposed algorithm compared with conventional watermarking algorithm by computer simulation. The experimental results show that the proposed watermarking algorithm is less visible to human eyes and more robust to image compressions, image processings, and geometric transformations than the conventional algorithm.

• Journal of Biomedical Engineering Research
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• v.21 no.3 s.61
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• pp.247-254
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• 2000

We propose an efficient MR image compression technique using fractal coding in wavelet transform domain. In the Proposed method , we construct significant coefficient trees with the absolute values of discrete wavelet transform coefficients and then perform the fractal coding with the information of significant coefficients having high energy. For MR images, most Pixels including background have very low gray level values, the number of significant coefficients is small. so we can expect high compression rate. In addition. since this method uses the fractal coding in wavelet transform domain, blocking artifact is reduced prominently and edges sensitive to human visual system are well preserved. As a result of computer simulation, we obtained the reconstructed images with better quality than those by JPEG at the low bit rates below 0.33[bpp].