• Title/Summary/Keyword: Vector compression

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Lossless VQ Indices Compression Based on the High Correlation of Adjacent Image Blocks

  • Wang, Zhi-Hui;Yang, Hai-Rui;Chang, Chin-Chen;Horng, Gwoboa;Huang, Ying-Hsuan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.8
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    • pp.2913-2929
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    • 2014
  • Traditional vector quantization (VQ) schemes encode image blocks as VQ indices, in which there is significant similarity between the image block and the codeword of the VQ index. Thus, the method can compress an image and maintain good image quality. This paper proposes a novel lossless VQ indices compression algorithm to further compress the VQ index table. Our scheme exploits the high correlation of adjacent image blocks to search for the same VQ index with the current encoding index from the neighboring indices. To increase compression efficiency, codewords in the codebook are sorted according to the degree of similarity of adjacent VQ indices to generate a state codebook to find the same index with the current encoding index. Note that the repetition indices both on the search path and in the state codebooks are excluded to increase the possibility for matching the current encoding index. Experimental results illustrated the superiority of our scheme over other compression schemes in the index domain.

Yielding Behavior of Compacted Decomposed Granitic Soil under Anisotropic Compression Previous Loading (비등방 압축의 선행재하를 받은 다짐풍화화강토의 항복거동)

  • Jeong, Sang-Guk;Kang, Kwon-Soo;Yang, Jae-Hyouk
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.5 no.3
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    • pp.233-244
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    • 2001
  • Stress-strain behaviour of soil varies based on stress path and stress history. There has been few study on the characteristics of yielding curve which has anisotropic compression stress history in decomposed granite soil. During this study, various stress path tests in previous anisotropic compression stress history are performed on compacted decomposed granite soil sampled at Iksan, Chonbuk. Yielding points are determined from various stress-strain curves (${\eta}-{\varepsilon}$, ${\eta}$-v, and ${\eta}$-k, ${\eta}$-W curves). Stress-strain curve is certified which shows yielding point very clearly. The shape and characteristics of anisotropic compression yielding curves are examined. The main results are summarized as follows : 1) p' constant and compressive direction in stress paths, which has experienced previous anisotropic compression stress history, shows relatively dear yielding points. 2) Yielding curves defined from ${\eta}$-k and ${\eta}$-W curve show almost perfect ellipse. 3) Directions of plastic strain incremental vector($dv^p/d{\varepsilon}^p$) are not perpendicular to yielding curve.

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On the Lower Level Laplacian Pyramid Image Coding Using Vector Quantization (벡터 양자화를 이용한 저층 라플라시안 피라미드 영상의 부호화에 관한 연구)

  • 김정규;정호열;최태영
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.17 no.3
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    • pp.213-224
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    • 1992
  • An encoding technique based on region splitting and vector quantization is proposed for the lower level Laplacian pyramid images. The lower level Laplacian pyramid images have lower variance than higher levels but a great influence on compression ration due to large spatial area. And so from data compression viewpoint, we subdivide them with variance thresholding into two regions such as one called : flat region” and the other “edge region”, and encode the flat region with its mean value and the edge region as vector quantization method. The edge region can be reproduced faithfully and significant improvement on compression ratio can be accomplished with a little degradation of PSNR in spite of the effect of large flat region since the codebook used is generated from the edge region only on from the entire image including the flat region. It can be verified by computer simulation results that proposed method is more efficient in compression ratio and processing time than the conventional encoding technique of vector quantization.

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Thresholding for CFD data compression based on Supercompact Multiwavelets (Supercompact Multiwavelets 을 이용한 CFD 데이터 압축의 Thresholding)

  • Kwon, Do-Hoon;Lee, Do-Hyung
    • Proceedings of the KSME Conference
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    • 2003.11a
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    • pp.962-967
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    • 2003
  • CFD data compression method based on supercompact multiwavelets is presented. High data compression can be achieved when taking advantage of the compact nature of multiwavelets. Thresholding technique is also a matter of primary concern in determining pressure ratio. In this paper, we apply thresholding for multiwavelets that considers the coefficient vector as a whole rather than thresholding individual elements. Various thresholding methods are described briefly. CFD data compression suggests that the multivariate thresholding method is suitable for supercompact multiwavelets.

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Intra-picture Block-matching Method for Codebook-based Texture Compression

  • Cui, Li;Jang, Euee S.
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.10
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    • pp.5063-5073
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    • 2016
  • In this paper, an efficient texture compression method is proposed for fast rendering, which exploits the spatial correlation among blocks through intra-picture block matching. Texture mapping is widely used to enhance the visual quality of results in real-time rendering applications. For fast texture mapping, it is necessary to identify an effective trade-off between compression efficiency and computational complexity. The conventional compression methods utilized for image processing (e.g., JPEG) provide high compression efficiency while resulting in high complexity. Thus, low complexity methods, such as ETC1, are often used in real-time rendering applications. Although these methods can achieve low complexity, the compression efficiency is still lower than that of JPEG. To solve this problem, we propose a texture compression method by reducing the spatial redundancy between blocks in order to achieve the better compression performance than ETC1 while maintaining complexity that is lower than that of JPEG. Experimental results show that the proposed method achieves better compression efficiency than ETC1, and the decoding time is significantly reduced compared to JPEG while similar to ETC1.

A Differential Index Assignment Scheme for Tree-Structured Vector Quantization (나무구조 벡터양자화 기반의 차분 인덱스 할당기법)

  • 한종기;정인철
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.28 no.2C
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    • pp.100-109
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    • 2003
  • A differential index assignment scheme is proposed for the image encoding system in which a variable-length tree-structured vector quantizer is adopted. Each source vector is quantized into a terminal node of VLTSVQ and each terminal node is represented as a unique binary vector. The proposed index assignment scheme utilizes the correlation between interblocks of the image to increase the compression ratio with the image quality maintained. Simulation results show that the proposed scheme achieves a much higher compression ratio than the conventional one does and that the amount of the bit rate reduction of the proposed scheme becomes large as the correlation of the image becomes large. The proposed encoding scheme can be effectively used to encode R images whose pixel values we, in general, highly correlated with those of the neighbor pixels.

Multispectral Image Compression Using Classification in Wavelet Domain and Classified Inter-channel Prediction and Selective Vector Quantization in Wavelet Domain (웨이브릿 영역에서의 영역분류와 대역간 예측 및 선택적 벡터 양자화를 이용한 다분광 화상데이타의 압축)

  • 석정엽;반성원;김병주;박경남;김영춘;이건일
    • Proceedings of the IEEK Conference
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    • 2000.06d
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    • pp.31-34
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    • 2000
  • In this paper, we proposed multispectral image compression method using CIP (classified inter-channel prediction) and SVQ (selective vector quantization) in wavelet domain. First, multispectral image is wavelet transformed and classified into one of three classes considering reflection characteristics of the subband with the lowest resolution. Then, for a reference channel which has the highest correlation with other channels, the variable VQ is performed in the classified intra-channel to remove spatial redundancy. For other channels, the CIP is performed to remove spectral redundancy. Finally, the prediction error is reduced by performing SVQ. Experiments are carried out on a multispectral image. The results show that the proposed method reduce the bit rate at higher reconstructed image quality and improve the compression efficiency compared to conventional method.

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Multispectral image data compression using wavelet transfrom and selective predicted vector quantization (웨이브릿 변환 및 선택적 예측 벡터 양자화를 이용한 다분광 화상데이타 압축)

  • 김병주;반성원;김경규;정원식;김영춘;이건일
    • Proceedings of the IEEK Conference
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    • 1998.06a
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    • pp.673-676
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    • 1998
  • Future land remote sensing satellite systems will kikely be constrained in terms of communication band-width. To alleviate this limitation, the data must be compressed. Image data obtained from satellite exhibit a high degree of spatial and spectral correlations that must be properly exploited. In this paper we propose multispectral image data compression using wavelet transform and selective predicted vector quantization. Th eproposed method is based on accuratly predicting other band from reference band and reducing bit rate through threshold map. we can achieve better compression effeciency than conventional methods.

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Wavelet-based Biomedical Signal Compression Using a Multi-stage Vector Quantization (다단계 벡터 양자화를 이용한 웨이브렛 기반 생체 신호 압축)

  • Park, Seo-Young;Kim, Young-Ju;Lee, In-Sung
    • Proceedings of the IEEK Conference
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    • 2006.06a
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    • pp.343-344
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    • 2006
  • In this paper, the biomedical signal compression method with multi-stage vector quantization is proposed. It utilizes characteristic of wavelet coefficients in which the energy is concentrated on approximation coefficients. The transmitted codebook index consists code vectors obtained by wavelet coefficients of ECG and Error signals from the 1024 block length, respectively. The proposed compression method showed 2.1298% in average PRD and 1.8 kbits/sec in CDR.

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Finite-state projection vector quantization applied to mean-residual compression of images (평균-잔류신호 영상압축에 적용된 유한 상태 투영벡터양자화)

  • 김철우;이충웅
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.21 no.9
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    • pp.2341-2348
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    • 1996
  • This paper proposes an image compression algorithm that adopts projection scheme on mean-residual metod. Sub-blocks of an image are encoded using mean-residual method where mean value is predicted according to that of neighboring blocks. Projection scheme with 8 directions is applied to the compression of residual signals of blocks. Projection vectors are finite-state vector quantized according to the projection angle of nighboring blocks in order to exploit the correlation among them. Side information to represent the repetition of projection is run-length coded while the information for projection direction is compressed using entropy encoding. The proposed scheme apears to be better in PSNR performance when compared with conventional projection scheme as well as in subjective quality preserving the edges of images better than most tranform methods which usually require heavy computation load.

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