Processing math: 100%
We use cookies to improve your experience with our site.

Indexed in:

SCIE, EI, Scopus, INSPEC, DBLP, CSCD, etc.

Submission System
(Author / Reviewer / Editor)
Advanced Search
Volume 21 Issue 3
May  2006
Turn off MathJax
Article Contents
Abstract
References
Related Articles
Si-Wei Ma, Wen Gao. Low Complexity Integer Transform and Adaptive Quantization Optimization[J]. Journal of Computer Science and Technology, 2006, 21(3): 354-359.
Citation: Si-Wei Ma, Wen Gao. Low Complexity Integer Transform and Adaptive Quantization Optimization[J]. Journal of Computer Science and Technology, 2006, 21(3): 354-359.
shu

Low Complexity Integer Transform and Adaptive Quantization Optimization

  • 1Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100080, P.R. China2Department of Computer Science, Harbin Institute of Technology, Harbin 150001, P.R. China

More Information
  • Received Date: October 30, 2005
  • Revised Date: March 07, 2006
  • Published Date: May 14, 2006
    Abstract
  • In this paper, a new low complexity integer transform is proposed, whichhas been adopted by AVS1-P7. The proposed transform can enable AVS1-P7to share the same quantization/dequantization table with AVS1-P2. As thebases of the proposed transform coefficients are very close, thetransform normalization can be implemented only on the encoder side andthe dequantization table size can be reduced compared with the transformused in H.264/MPEG-4 AVC. Along with the feature of the proposedtransform, adaptive dead-zone quantization optimization for the proposedtransform is studied. Experimental results show that the proposedinteger transform has similar coding performance compared with thetransform used in H.264/MPEG-4 AVC, and would gain near 0.1dB with theadaptive dead-zone quantization optimization.
    • FullText(HTML)
    • References (18)
  • [1]
    Tran T D. The BinDCT: Fast multiplierless approximation of the DCT. IEEE Signal Processing Letters, 2000, 7(6): 141--144.
    [2]
    Chen Y J, Oraintara S, Tran T D et al. Multiplierless approximation of transforms with adder constraint. IEEE Signal Processing Letters, 2002, 9(11): 344--347.
    [3]
    Chen Y J, Oraintara S, Nguyen T Q. Video compression using integer DCT. In Proc. Int. Conf. Image Processing, Vancouver, Canada, September 10--13, 2000, pp.844--845.
    [4]
    Bjontegaard G. Coding improvement by using 4∗4 blocks for motion vectors and transform. ftp://ftp3.itu.int/video-site/9712_Eib/q15c23.doc.
    [5]
    Wien M, Sun S J. ICT comparison for adaptive block transform. ftp://ftp3.itu.int/video-site/0101_Eib/ VCEG-L12.doc.
    [6]
    Hallapuro A, Karczewicz M, Malvar H. Low complexity transform and quantization---Part I: Basic implementation. ftp://ftp3.itu.int/video-site/0201_Gen/JVT-B038.doc.
    [7]
    Hallapuro A, Karczewicz M, Malvar H. Low complexity transform and quantization---Part II: Extensions. ftp://ftp3.itu.int/video-site/0201_Gen JVT-B039.doc.
    [8]
    Wien M. Clean-up and improved design consistency for ABT. ftp://ftp3.itu.int/jvt-site/2002_10_Geneva/JVT-E025.doc.
    [9]
    Malvar H S. Low-complexity length-4 transform and quantization with 16-bit arithmetic. ftp://ftp.imtc-files.org/jvt-experts/0109_San/VCEG-N44.doc.
    [10]
    Gordon S, Marpe D, Wiegand T. Simplified use of 8∗8 transforms---proposal. ftp://ftp3.itu.int/jvt-site/2003_ 12_Waikoloa/JVT-J029.doc.
    [11]
    Gordon S, Marpe D, Wiegand T. Simplified use of 8∗8 transforms---updated proposal and results. ftp://ftp3.itu. int/jvt-site/2004_03_Munich/JVT-K028.doc.
    [12]
    Zhang C X, Lou J, Yu L et al. The techniques of pre-scaled integer transform. In Proc. Int. Symp. Circuits and Systems, Kobe, Japan. May 23--26, 2005, pp.316--319.
    [13]
    Lou J, Dong J, Yu L. 8∗8 integer transform. ftp://159.226.42.57/pulic/AVS_ M1182.doc.
    [14]
    Wiegand T. H.26L Test Model Long-Term Number 9 (TML-9) draft0. ftp://ftp.imtc-files.org/0109_San/VCEG-N83 d1.doc.
    [15]
    Wien M, Sun S J. ICT comparison for adaptive block transforms. ftp://ftp.imtc-files.org/jvt-experts/0109_San/VCEG-L12.doc.
    [16]
    Tourapis A M, Boyce J. Performance evaluation of the 8∗8 transform vs. coefficient adaptive deadzone. ftp://ftp.imtc-files.org/jvt-experts/0403_Munich/JVT-K035.doc.
    [17]
    Sullivan G. Adaptive quantization encoding technique using an equal expected-value rule. ftp://ftp3.itu.int/jvt-site/2005_01_HongKong/JVT-N011.doc.
    [18]
    AVS FTP Site. ftp://159.226.42.57.
    • Relative Articles

  • Related Articles

    [1]Cheng Gong, Ye Lu, Su-Rong Dai, Qian Deng, Cheng-Kun Du, Tao Li. AutoQNN: An End-to-End Framework for Automatically Quantizing Neural Networks[J]. Journal of Computer Science and Technology, 2024, 39(2): 401-420. DOI: 10.1007/s11390-022-1632-9
    [2]Dong-Di Zhao, Fan Li, Kashif Sharif, Guang-Min Xia, Yu Wang. Space Efficient Quantization for Deep Convolutional Neural Networks[J]. Journal of Computer Science and Technology, 2019, 34(2): 305-317. DOI: 10.1007/s11390-019-1912-1
    [3]Shu-Chang Zhou, Yu-Zhi Wang, He Wen, Qin-Yao He, Yu-Heng Zou. Balanced Quantization: An Effective and Efficient Approach to Quantized Neural Networks[J]. Journal of Computer Science and Technology, 2017, 32(4): 667-682. DOI: 10.1007/s11390-017-1750-y
    [4]HE Simin, ZHANG Bo. Solving SAT by Algorithm Transform of Wu s Method[J]. Journal of Computer Science and Technology, 1999, 14(5): 468-480.
    [5]Hu zhanyi, YANG Changjiang, YANG Yi, MA Songde. An Inherent Probabilistic Aspect of the Hough Transform[J]. Journal of Computer Science and Technology, 1999, 14(1): 44-48.
    [6]Lin Xueyin, Chen Xiangrong, Zhu Zhigang, Shi Dingji. Range Information Propagation Transform[J]. Journal of Computer Science and Technology, 1998, 13(5): 438-447.
    [7]Hu Zhanyi, Wang Wei, Yang Yi, Ma Songde. A New Definition of the Hough Transform[J]. Journal of Computer Science and Technology, 1998, 13(5): 385-392.
    [8]Jiang Tianzi, Ma Songde. Contour Matching Using Wavelet Transform and Multigrid Methods[J]. Journal of Computer Science and Technology, 1997, 12(6): 564-570.
    [9]Wang Zhou, Yu Yinglin. Dynamic Fractal Transform with Applications to Image Data Compression[J]. Journal of Computer Science and Technology, 1997, 12(3): 202-209.
    [10]Hu Zhanyi, Ma Songde. Performance Prediction of the Hough Transform[J]. Journal of Computer Science and Technology, 1997, 12(1): 49-57.
    • Supplements (0)

Catalog

    Get Citation
    XML
    Article views (26) PDF downloads (2155) Cited by()
    Related

    Copyright ©2025 JCST, All Rights Reserved     京ICP备05002829号-1

    Institute of Computing Technology, Chinese Academy of Sciences
    P.O. Box 2704, Beijing 100190, P.R. China

    Tel.: 86-10-62610746 E-mail: jcst@ict.ac.cn

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return