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Quality control method of the transmission of fine image details in the JPEG2000

S.V. Sai  1, A.G. Shoberg  1

1 Pacific National University, Khabarovsk, Russia

 PDF, 1016 kB

DOI: 10.18287/2412-6179-CO-616

Pages: 401-408.

Full text of article: Russian language.

Abstract:
The article proposes a method for controlling the transmission quality of fine image details in the JPEG2000 standard based on an automatic adjustment of the quantization parameters of discrete wavelet transform (DWT) coefficients. An algorithm for setting up quantization scale parameters for different transformation sub-ranges of the DWT coefficients depending on given (permissible) distortions is described. For an objective assessment of image quality, numerical measures of fine detail distortion in a normalized N-CIELAB colorimetric system are used, according to which an analysis of their structural features is performed. Results of the experimental studies of the analysis of image quality and compression efficiency depending on the quantization parameters utilized in the developed adaptive compression algorithm are presented. Results of evaluating the algorithm performance that can be used for practical applications in multimedia applications are also presented.

Keywords:
image analysis, distortion metric, discrete wavelet transform, quantization, JPEG2000.

Citation:
Sai SV, Shoberg AG. Quality control method of the transmission of fine image details in the JPEG2000. Computer Optics 2020; 44(3): 401-408. DOI: 10.18287/2412-6179-CO-616.

References:

  1. Liu G, Zeng X, Tian F, Chaibou K, Zheng Z. A novel direction adaptive wavelet based image compression. AEU – Int J Electron Commun 2010; 64(6): 531-539.
  2. Al-Azawi S, Boussakta S, Yakovlev A. Image compression algorithms using intensity based adaptive quantization coding. Am J Engineer Appl Sci 2014; 4(4): 504-512.
  3. Chen P-Y, Chang J-Y. An adaptive quantization scheme for 2-D DWT coefficients. Int J Appl Sci Eng 2013; 11(1): 85-100.
  4. Dvorkovich VP, Dvorkovich AV. Calculation of filter banks for discrete wavelet transform and analysis of their characteristics [In Russian]. Digital Signal Processing 2006; 2: 2-10.
  5. Umnyashkin SV, Gizyatulin RR. Compression of images based on block decomposition in the field of packet wavelet transform [In Russian]. Digital Signal Processing 2014; 1: 46-51.
  6. Lin W, Kuo C-CJ. Perceptual visual quality metrics: A survey. Visual Communication and Image Representation 2011; 22(4): 297-312.
  7. Bovik A, Mittal A. No-reference image quality assessment in the spatial domain. IEEE Trans Image Process 2012; 21(12): 4695-4708.
  8. Sai SV. Metric of fine structures distortions of compressed images. Computer Optics. 2018; 42(5): 829-837. DOI: 10.18287/2412-6179-2018-42-5-829-837.
  9. Drozdov SN, Zhiglaty AA, Kravchenko PP, Lutai VN, Skorokhod SN, Khusainov NS. JPEG2000 standard: basic algorithms, implementation examples, and application prospects [In Russian]. Rostov-on-Don: Publishing House of SFU, 2014.
  10. Taubman D, Marcellin MD. JPEG2000 image compression fundamentals, standard and practice. Kluver Academic Publishers; 2002.
  11. Balster EJ, Fortener BT, Turri WF. Post-compression rate-distortion development for embedded block coding with optimal truncation in JPEG2000 imagery. International Journal of Image and Graphics 2011; 11(4): 611-627.
  12. Koltsov PP, Osipov AS, Kutsaev AS, Kravchenko AA, Kotovich NV, Zakharov AB. On the quantitative performance evaluation of image analysis algorithms. Computer Optics 2015; 39(4): 542-556. DOI: 10.18287/0134-2452-2015-39-4-542-556.
  13. Fairchild MD. Color appearance models. John Wiley and Sons; 2005.
  14. Sai SV, Sorokin NYu, Shoberg AG. Segmentation of fine details in the CIELAB. 24th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision (WSCG) 2016: 155-162.
  15. Sai SV, Savenkov IV. Selection of threshold selection coefficients for color image wavelet transforms. Informatics and Control Systems 2001; 2: 112-117.
  16. Image & video quality assessment at LIVE. Source: <http://live.ece.utexas.edu/research/quality/>.
  17. Myasnikov BB. Efficient algorithms for local discrete wavelet transform. Computer Optics 2007; 31(4): 86-94. Export compliance metrics for Intel® microprocessors.
  18. Intel. Support. Source: <https://www.intel.com/content/www/us/en/support/articles/000005755/processors.html>.

 

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