• Title/Summary/Keyword: entropy coding

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Non-fixed Quantization Considering Entropy Encoding in HEVC (HEVC 엔트로피 부호화를 고려한 비균등 양자화 방법)

  • Gweon, Ryeong-Hee;Han, Woo-Jin;Lee, Yung-Lyul
    • Journal of Broadcast Engineering
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    • v.16 no.6
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    • pp.1036-1046
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    • 2011
  • MPEG and VCEG have constituted a collaboration team called JCT-VC(Joint Collaborative Team on Video Coding) and have been developing HEVC(High Efficiency Video Coding) standard. All transform coefficients in a TU(Transform Unit) have been equally quantized according to the quantization and inverse quantization method which is used in HEVC standard. Such an equal quantization is not efficient because the transformed coefficients in the TU are not eqully distributed. Furthermore, the quantized coefficients which is positioned in later scanning order cannot be efficient due to the entropy scanning method. We suggest an algorithm that transform coefficients are quantized at different values according to the position in TU considering a scanning order of entropy encoding to improve the coding efficiency. The principle of this algorithm is that quantization and inverse quantization are carried out according to the scanning order which is in accordance with the statistical characteristic of distribution of quantized transform coefficients. The proposed algorithm shows on the average of 0.34% Y BD-rate compression rate improvement.

Context-based Predictive Coding Scheme for Lossless Image Compression (무손실 영상 압축을 위한 컨텍스트 기반 적응적 예측 부호화 방법)

  • Kim, Jongho;Yoo, Hoon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.17 no.1
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    • pp.183-189
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    • 2013
  • This paper proposes a novel lossless image compression scheme composed of direction-adaptive prediction and context-based entropy coding. In the prediction stage, we analyze the directional property with respect to the current coding pixel and select an appropriate prediction pixel. In order to further reduce the prediction error, we propose a prediction error compensation technique based on the context model defined by the activities and directional properties of neighboring pixels. The proposed scheme applies a context-based Golomb-Rice coding as the entropy coding since the coding efficiency can be improved by using the conditional entropy from the viewpoint of the information theory. Experimental results indicate that the proposed lossless image compression scheme outperforms the low complexity and high efficient JPEG-LS in terms of the coding efficiency by 1.3% on average for various test images, specifically for the images with a remarkable direction the proposed scheme shows better results.

A Frame-based Coding Mode Decision for Temporally Active Video Sequence in Distributed Video Coding (분산비디오부호화에서 동적비디오에 적합한 프레임별 모드 결정)

  • Hoangvan, Xiem;Park, Jong-Bin;Shim, Hiuk-Jae;Jeon, Byeung-Woo
    • Journal of Broadcast Engineering
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    • v.16 no.3
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    • pp.510-519
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    • 2011
  • Intra mode decision is a useful coding tool in Distributed Video Coding (DVC) for improving DVC coding efficiency for video sequences having fast motion. A major limitation associated with the existing intra mode decision methods, however, is that its efficiency highly depends on user-specified thresholds or modeling parameters. This paper proposes an entropy-based method to address this problem. The probabilities of intra and Wyner?Ziv (WZ) modes are determined firstly by examining correlation of pixels in spatial and temporal directions. Based on these probabilities, entropy of the intra and the WZ modes are computed. A comparison based on the entropy values decides a coding mode between intra coding and WZ coding without relying on any user-specified thresholds or modeling parameters. Experimental results show its superior rate-distortion performance of improvements of PSNR up to 2 dB against a conventional Wyner?Ziv coding without intra mode decision. Furthermore, since the proposed method does not require any thresholds or modeling parameters from users, it is very attractive for real life applications.

A VLSI Design of Entropy Coding Algorithm for JPEG2000 CODEC (JPEG2000 CODEC을 위한 Entropy 코딩 알고리즘의 VLSI 설계)

  • Lee, Kyoung-Min;Oh, Kyoung-Ho;Jung, Il-Hwan;Kim, Young-Min
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.1C
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    • pp.35-44
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    • 2004
  • In this paper, we design an efficient VLSI architecture of entropy coding algorithm in JPEG2000. Entropy coder is a context-based binary arithmetic encoder, and composed of a Context Extractor(CE) and an Arithmetic Coder(AC). We speed-up CE by skipping no-operation bits in coding passes, and AC is to be performed based on MQ coder. Because of using Qe value associated with each allowed context and probability estimation, MQ coder is a multiplication free coder that reduces computation loads and makes simple the structure of arithmetic coder. We have developed and synthesized the VHDL models of CE and AC pairs using Xilinx FPGA technology. The proposed architecture operates up to 30MHz.

Entropy-Constrained Temporal Decomposition (엔트로피 제한 조건을 갖는 시간축 분할)

  • Lee Ki-Seung
    • The Journal of the Acoustical Society of Korea
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    • v.24 no.5
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    • pp.262-270
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    • 2005
  • In this paper, a new temporal decomposition method is proposed. where not oniy distortion but also entropy are involved in segmentation. The interpolation functions and the target feature vectors are determined by a dynamic Programing technique. where both distortion and entropy are simultaneously minimized. The interpolation functions are built by using a training speech corpus. An iterative method. where segmentation and estimation are iteratively performed. finds the locally optimum Points in the sense of minimizing both distortion and entropy. Simulation results -3how that in terms of both distortion and entropy. the Proposed temporal decomposition method Produced superior results to the conventional split vector-quantization method which is widely employed in the current speech coding methods. According to the results from the subjective listening test, the Proposed method reveals superior Performance in terms of qualify. comparing to the Previous vector quantization method.

A New Image Coding Technique with Low Entropy

  • Joo, S.H.;H.Kikuchi;S.Sasaki;Shin, J.
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 1998.06b
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    • pp.189-194
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    • 1998
  • We introduce a new zerotree scheme that effectively exploits the inter-scale self-similarities found in the octave decomposition by a wavelet transform. A zerotree is useful to efficiently code wavelet coefficients and its efficiency was proved by Shapiro's EZW. In the coding scheme, wavelet coefficients are symbolized and entropy-coded for more compression. The entropy per symbol is determined from the produced symbols and the final coded size is calculated by multiplying the entropy and the total number of symbols. In this paper, were analyze produced symbols from the EZW and discuss the entropy per symbol. Since the entropy depends on the produced symbols, we modify the procedure of symbolic streaming out for the purpose. First, we extend the relation between a parent and children used in the EZW to raise a probability that a significant parent has significant children. The proposed relation is flexibly extended according to the fact that a significant coefficient is highly addressed to have significant coefficients in its neighborhood. The extension way is reasonable because an image is decomposed by convolutions with a wavelet filter and thus neighboring coefficients are not independent with each other.

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Classified Image Compression and Coding using Multi-Layer Percetpron (다층구조 퍼셉트론을 이용한 분류 영상압축 및 코딩)

  • 조광보;박철훈;이수영
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.19 no.11
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    • pp.2264-2275
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    • 1994
  • In this paper, image compression based on neural networks is presented with block classification and coding. Multilayer neural networks with error back-propagation learning algorithm are used to transform the normalized image date into the compressed hidden values by reducing spatial redundancies. Image compression can basically be achieved with smaller number of hidden neurons than the numbers of input and output neurons. Additionally, the image blocks can be grouped for adaptive compression rates depending on the characteristics of the complexity of the blocks in accordance with the sensitivity of the human visual system(HVS). The quantized output of the hidden neuron can also be entropy coded for an efficient transmission. In computer simulation, this approach lie in the good performances even with images outside the training set and about 25:1 compression rate was achieved using the entropy coding without much degradation of the reconstructed images.

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A Ranking Method for Improving Performance of Entropy Coding in Gray-Level Images (그레이레벨 이미지에서의 엔트로피 코딩 성능 향상을 위한 순위 기법)

  • You, Kang-Soo;Sim, Chun-Bo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.12 no.4
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    • pp.707-715
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    • 2008
  • This paper proposes an algorithm for efficient compression gray-level images by entropy encoder. The issue of the proposed method is to replace original data of gray-level images with particular ranked data. For this, first, before encoding a stream of gray-level values in an image, the proposed method counts co-occurrence frequencies for neighboring pixel values. Then, it replaces each pay value with particularly ranked numbers based on the investigated co-occurrence frequencies. Finally, the ranked numbers are transmitted to an entropy encoder. The proposed method improves the performance of existing entropy coding by transforming original gray-level values into rank based images using statistical co-occurrence frequencies of gray-level images. The simulation results, using gray-level images with 8-bits, show that the proposed method can reduce bit rate by up to 37.85% compared to existing conventional entropy coders.

A conditional entropy codingscheme for tree structured vector quantization (나무구조 벡터양자화를 위한 조건부 엔트로피 부호화기법)

  • 송준석;이승준;이충웅
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.22 no.2
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    • pp.344-352
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    • 1997
  • This paper proposes an efficient lossless coding scheme for tree structured vector quantization (TSVQ) system which efficiently exploits inter-block correlation. The TSVQ index of the current block is adaptively arithmeticencoded depending on the indices of the previous blocks. This paper also presents a reductio method, which effectively resolve the memory problem which usually arises in many conditional entropy coding schemes. Simulation results show that the proposed scheme provides remarkable bitrate reduction by effectively exploiting not only linear but also non-linear inter-block correlation.

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SMOOTHLY PERFECT 8-CONNECTED CONTOUR AND ITS CODING TECHNIQUE (평활한 완전 8방향 윤곽선과 이의 부호화 기법)

  • 조성호;김인철;이상욱
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 1996.06a
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    • pp.195-198
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    • 1996
  • In this paper, we introduce the notion of the smoothly perfect 8-connected (SP8C) contour and propose a coding technique for the SP8C contours. Based on the contour simplification using the majority filter proposed by Gu[6], SP8C contours are extracted on the contour lattice from the segmented image. By noting that, unlike the perfect 8-connected contours, the SP8C contours are restricted to travel in only 3 different directions along the contours, we also propose two techniques for encoding the SP8C contours. The one is the modified version of the neighbouring direction segment coding by Kandeko[2], while the other is to employ the notion of the entropy coding. From the comparison in terms of the entropy, it is shown that the proposed SP8C contours require les bits in encoding the diagonal contours than the 4-connected contours employed by Gu. And computer simulations reveal that the contours can be efficiently encoded by the proposed technique.

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