• 대한전자공학회논문지
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• 제12권2호
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• pp.1-10
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• 1975

본 논문은 사진데이타에 쉽게 적용할수있는 한 adaptive data compression 방법을 노표시하였다. 이웃 sample data 사이의 높은 correlation때문에 발생할 부호화 복잡성을 간편한 sample difference data로 대처하였으며, 자단의 statistical nonstationarity에 적응키 위해서 여덟가지 부호(code)로 구성된 code set중에서 최적부호를 선택토록 하였다. code erst는 두가지 등장부호와 여섯가지 보완형 Shannon-Fanro 부호로 되었다. difference data의 확률분포는 Laplacian model로, entropy의 확률분포는 Gaussian model대 하였다. 부호선별 Paranleter로서 entropy와 Pr[차이값=0]=Po를 비교하였다. 콤퓨타 실험결과 이 adaptive coding 방법으로 2대 1의 데이타 감축비를 얻었다. 이 방법은 fixed coding에 비해서 데이타 감축비와 부호화효율에서 약 10%와 15%의 이득을 주었다. 또한 도는 entropy보다 휠신 편리한 부호선별 parameter인 중시에 entropy 경우와 1% 내외의 좋은 결과를 얻을수 있음이 확인되었다. This paper presents an adaptive data compression algorithm for video data. The coling complexity due to the high correlation in the given data sequence is alleviated by coding the difference data, sequence rather than the data sequence itself. The adaptation to the nonstationary statistics of the data is confined within a code set, which consists of two constant length cades and six modified Shannon·Fano codes. lt is assumed that the probability distributions of tile difference data sequence and of the data entropy are Laplacian and Gaussion, respectively. The adaptive coding performance is compared for two code selection criteria: entropy and pr[difference value=0]=po. It is shown that data compression ratio 2 : 1 is achievable with the adaptive coding. The gain by the adaptive coding over the fixed coding is shown to be about 10% in compression ratio and 15% in code efficiency. In addition, po is found to he not only a convenient criterion for code selection, but also such efficient a parameter as to perform almost like entropy.

• Journal of applied mathematics & informatics
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• 제8권3호
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• pp.881-888
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• 2001

Recently, Hooda and Ram [7] have proposed and characterized a new generalized measure of R-norm entropy. In the present communication we have studied its application in coding theory. Various mean codeword lengths and their bounds have been defined and a coding theorem on lower and upper bounds of a generalized mean codeword length in term of the generalized R-norm entropy has been proved.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 1999년도 KOBA 방송기술 워크샵 KOBA Broadcasting Technology Workshop
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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.

• 한국산학기술학회논문지
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• 제11권1호
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• pp.209-213
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• 2010

본 논문에서 엔트로피 코딩을 위한 효과적인 예측기를 제안한다. 제안하는 예측기는 MED(median edge detector)와 GAP(gradient adaptive prediction)의 예측 에러 중의 하나를 적응적으로 선택한다. 감소한 에러는 기존의 엔트로피 코딩 방법을 이용하여 부호화한다. 실험 결과, 제안하는 알고리즘이 기존 예측 방법보다 향상된 압축이 가능함을 보인다.

• Journal of Multimedia Information System
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• 제5권4호
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• pp.273-276
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• 2018

In video compression standards, the entropy coding is essential to the high performance compression because redundancy of data symbols is removed. Binary arithmetic coding is one of high performance entropy coding methods. However, the dependency between consecutive binary symbols prevents improving the throughput. For the throughput enhancement, a new probability model is proposed for encoding multi-symbols at one time. In the proposed method, multi-symbol encoder is implemented with only adders and shifters, and the multiplication table for interval subdivision of binary arithmetic coding is removed. Compared to the compression ratio of CABAC of H.264/AVC, the performance degradation on average is only 1.4% which is negligible.

• IEIE Transactions on Smart Processing and Computing
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• 제6권4호
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• pp.292-298
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• 2017

The complexity of image compression algorithms has increased in order to improve image compression efficiency. One way to resolve high computational complexity is parallel processing. However, entropy coding, which is lossless compression, does not fit into the parallel processing form because of the correlation between consecutive symbols. This paper proposes a new application-specific instruction set processor (ASIP) platform by adding new context-adaptive binary arithmetic coding (CABAC) instructions to the existing platform to quickly process a variety of entropy coding. The newly added instructions work without conflicts with all other existing instructions of the platform, providing the flexibility to handle many coding standards with fast processing speeds. CABAC software is implemented for High Efficiency Video Coding (HEVC) and the performance of the proposed ASIP platform was verified with a field programmable gate array simulation.

• 대한전자공학회논문지
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• 제21권6호
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• pp.115-117
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• 1984

이중 run-length 부호화에서 run-length의 최대값이 M으로 제한되었을 때의 최대 entropy를 구하는 과정을 보였고, 이때 M이 무한대가 되면 Huang의 상한이 된다.

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2004년도 Asia Display / IMID 04
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• pp.149-152
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• 2004

A new joint source channel coding reduces both input-width and average current consumption to transmit image data to LCD source drivers. As a source coding, it is based on entropy coding of differential pulse code modulation scheme, especially using median edge detector of image predictor. As a channel coding, it is not a simple pulse amplitude modulation, but linked by source entropy to reduce average amplitude. Simulation results show 1/4 width is achievable by 16-valued transmission with keeping conventional current consumption (0.36 to 1.3).

• 한국컴퓨터정보학회논문지
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• 제21권5호
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• pp.31-40
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• 2016

In this paper, we analyse the characteristics of the edge image and propose a new entropy coding optimized to the compression of the edge image. The pixel values of the edge image have the Gaussian distribution around '0', and most of the pixel values are '0'. By using this analysis, the Zero Block technique is utilized in spatial domain. And the Intra Prediction Mode of the edge image is similar to the mode of the surrounding blocks or likely to be the Planar Mode or the Horizontal Mode. In this paper, we make use of the MPM technique that produces the Intra Prediction Mode with high probability modes. By utilizing the above properties, we design a new entropy coding method that is suitable for edge image and perform the compression. In case the existing compression techniques are applied to edge image, compression ratio is low and the algorithm is complicated as more than necessity and the running time is very long, because those techniques are based on the natural images. However, the compression ratio and the running time of the proposed technique is high and very short, respectively, because the proposed algorithm is optimized to the compression of the edge image. Experimental results indicate that the proposed algorithm provides better visual and PSNR performance up to 11 times than the JPEG.

• 스마트미디어저널
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• 제1권2호
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• pp.6-11
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• 2012

HEVC 표준에서 변환 계수 부호화 과정은 비트스트림에 포함되는 정보를 직접 부호화하는 핵심 부분으로 변환 계수 주사와 엔트로피 부호화를 포함한다. 최근, JCT-VC(Joint Collaborative Team on Video Coding)는 HEVC 위원회 초안(Committee Draft)을 완성했다. 본 논문에서는 HEVC 표준의 변환 계수 부호화 기술을 설명하고, 화면내 부호기에서의 변환 계수 발생확률을 고려한 효율적인 변환 계수 부호화 기술을 제안한다. 제안하는 방법은 기존 HEVC 변환 계수 부호화 기술에 비해 평균 0.74%의 BD-Rate를 절약한다.