• Title/Summary/Keyword: lossless compress

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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.

Predictor Switching Algorithm for Lossless Compression (무손실 압축을 위한 예측기 스위칭 알고리즘)

  • Kim, Young-Ro;Yi, Joon-Hwan
    • 전자공학회논문지 IE
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    • v.47 no.2
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    • pp.27-31
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    • 2010
  • In this paper, a predictor switching algorithm for lossless compression is proposed. It uses adaptively one of two predictors using errors obtained by MED(median edge detector) and GAP(gradient adaptive prediction). The reduced error is measured by existing entropy method. Experimental results show that the proposed algorithm can compress higher than existing predictive methods.

Development of the Lossless Biological Signal Compression Program for High-quality Multimedia based Real-Time Emergency Telemedicine Service (고품질 멀티미디어 기반 응급 원격 진료서비스를 위한 생체신호 무손실 압축, 복원 프로그램 개발)

  • Lim, Young-Ho;Kim, Jung-Sang;Yoon, Tae-Sung;Yoo, Sun-Kook
    • Proceedings of the KIEE Conference
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    • 2002.07d
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    • pp.2727-2729
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    • 2002
  • In an emergency telemedicine system such as High-quality Multimedia based Real-time Emergency Telemedicine(HMRET) service, it is very important to examine the status of the patient continuously using the multimedia data including the biological signals(ECG, BP, Respiration, $SpO_2$) of the patient. In order to transmit these data real time through the communication means which have the limited transmission capacity. It is also necessary to compress the biological data besides other multimedia data. For the HMRET service, we developed the lossless biological signal compression program in MSVC++ 6.0 using DPCM method and JPEG Huffman table, and tested in an internet environment.

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The Study on Lossy and Lossless Compression of Binary Hangul Textual Images by Pattern Matching (패턴매칭에 의한 이진 한글문서의 유.무손실 압축에 관한 연구)

  • 김영태;고형화
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.22 no.4
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    • pp.726-736
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    • 1997
  • The textual image compression by pattern matching is a coding scheme that exploits the correlations between patterns. When we compress the Hangul (Korean character) text by patern matching, the collerations between patterns may decrease due to randoem contacts between phonemes. Therefore in this paper we separate connected phonemes to exploit effectively the corrlation between patterns by inducting the amtch. In the process of sequation, we decide whether the patterns have vowel component or not, and then vowels connected with consonant ae separated. When we compare the proposed algorithm with the existing algorith, the compression ratio is increased by 1.3%-3.0% than PMS[5] in lossy mode, by 3.4%-9.1% in lossless mode than that of SPM[7] which is submitted to standard committe for second generation binary compression algorithm.

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A Lossless Image Compression using Wavelet Transform with 9/7 Integer Coefficient Filter Bank (9/7텝을 갖는 정수 웨이브릿 변환을 이용한 무손실 정지영상 압축)

  • 추형석;서영천;이태호;전희성;안종구
    • Proceedings of the Korea Institute of Convergence Signal Processing
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    • 2000.08a
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    • pp.253-256
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    • 2000
  • In this paper, we propose the lossless image compression algorithm using the integer wavelet transform. Recently, the S+P transform is widely used and computed with only integer addition and bit-shift operations, but not proper to remove the correlation of smooth images. then we compare the Harr wavelet of the S+P transform with various integer coefficient filter banks and apply 9/7 ICFB to the wavelet transform. In addition, we propose a entropy-coding method that exploits the multiresolution structure and the feedback of the prediction error, and can efficiently compress the transformed image for progressive transmission. Simulation results are compared to the compression ratio using the S+P transform with different types of images.

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Lossless Compression and Rendering of Multiple Layer Displacement Map (다층 변위 맵의 비손실 압축과 렌더링)

  • Chun, Young-Jae;Kim, Hae-Dong;Cho, Sung-Hyun
    • Journal of Korea Game Society
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    • v.9 no.6
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    • pp.171-178
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    • 2009
  • Multiple layer displacement mapping methods are able to represent more complex and general geometries which cannot be presented by single layer displacement mapping methods, and provide a realistic scene to digital contents such as 3D games and movies with relatively low costs. However, as we use more layers for details, data space is wasted more because lower layers have less displacement data than higher layers. In this paper, we suggest a lossless compression and rendering method of a multiple layer displacement map. Since we compress the map without data loss, the proposed method provides the same quality as the rendering result that uses an original multiple layer displacement map.

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An Improvement of Lossless Image Compression for Mobile Game (모바일 게임을 위한 개선된 무손실 이미지 압축)

  • Kim Se-Woong;Jo Byung-Ho
    • The KIPS Transactions:PartB
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    • v.13B no.3 s.106
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    • pp.231-238
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    • 2006
  • In this paper, the method to make lossless image compression that holds considerable part of total volume of mobile game has been proposed. To increase the compression rate, we compress the image by Deflate algorithm defined in RFC 1951 after reorganize it at preprocessing stage before conducting actual compression. At the stage of preprocessing, we obtained the size of a dictionary based on the information of image which is the feature of Dictionary-Based Coding, and increased the better compression rate than compressing in a general manner using in a way of restructuring image by pixel packing method and DPCM prediction technique. It has shown that the method increased 9.7% of compression rate compare with existing mobile image format, after conducting the test of compression rate applying the suggested compression method into various mobile games.

Adaptive Medical Image Compression Based on Lossy and Lossless Embedded Zerotree Methods

  • Elhannachi, Sid Ahmed;Benamrane, Nacera;Abdelmalik, Taleb-Ahmed
    • Journal of Information Processing Systems
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    • v.13 no.1
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    • pp.40-56
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    • 2017
  • Since the progress of digital medical imaging techniques, it has been needed to compress the variety of medical images. In medical imaging, reversible compression of image's region of interest (ROI) which is diagnostically relevant is considered essential. Then, improving the global compression rate of the image can also be obtained by separately coding the ROI part and the remaining image (called background). For this purpose, the present work proposes an efficient reversible discrete cosine transform (RDCT) based embedded image coder designed for lossless ROI coding in very high compression ratio. Motivated by the wavelet structure of DCT, the proposed rearranged structure is well coupled with a lossless embedded zerotree wavelet coder (LEZW), while the background is highly compressed using the set partitioning in hierarchical trees (SPIHT) technique. Results coding shows that the performance of the proposed new coder is much superior to that of various state-of-art still image compression methods.

Lossless Image Compression Using Block-Adaptive Context Tree Weighting (블록 적응적인 Context Tree Weighting을 이용한 무손실 영상 압축)

  • Oh, Eun-ju;Cho, Hyun-ji;Yoo, Hoon
    • Journal of Internet Computing and Services
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    • v.21 no.4
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    • pp.43-49
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    • 2020
  • This paper proposes a lossless image compression method based on arithmetic coding using block-adaptive Context Tree Weighting. The CTW method predicts and compresses the input data bit by bit. Also, it can achieve a desirable coding distribution for tree sources with an unknown model and unknown parameters. This paper suggests the method to enhance the compression rate about image data, especially aerial and satellite images that require lossless compression. The value of aerial and satellite images is significant. Also, the size of their images is huger than common images. But, existed methods have difficulties to compress these data. For these reasons, this paper shows the experiment to prove a higher compression rate when using the CTW method with divided images than when using the same method with non-divided images. The experimental results indicate that the proposed method is more effective when compressing the divided images.

Implement of Integration Compression Environment System Compressing Medical Images (의료영상 압축을 위한 통합압축환경시스템 구현)

  • 추은형;박무훈
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.7 no.1
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    • pp.142-148
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    • 2003
  • We compress medical images in order to solve problems both of request of storage mediums and of a low network speed. In this paper, integration compression environment has been developed for unity of various compression methods. Various compression methods that are implemented by integration compression environment, RLC, Lossless JPEG, and JPEG, comply with the DICOM 3.0. A compression method using DWT is implemented at it. And a unit method of Lossless compression method and lossy compression method is designed to improve images quality and to progress compression ratio. Diverse medical images can be compressed by each compression method. And integration compression environment is operated together database so that information of medical images is administered.