Browse > Article
http://dx.doi.org/10.3837/tiis.2018.10.023

JPEG-based Variable Block-Size Image Compression using CIE La*b* Color Space  

Kahu, Samruddhi Y. (Department of Electronics and Communication Engg., Visvesvaraya National Institute of Technology)
Bhurchandi, Kishor M. (Department of Electronics and Communication Engg., Visvesvaraya National Institute of Technology)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.12, no.10, 2018 , pp. 5056-5078 More about this Journal
Abstract
In this work we propose a compression technique that makes use of linear and perceptually uniform CIE $La^*b^*$ color space in the JPEG image compression framework to improve its performance at lower bitrates. To generate quantization matrices suitable for the linear and perceptually uniform CIE $La^*b^*$ color space, a novel linear Contrast Sensitivity Function (CSF) is used. The compression performance in terms of Compression Ratio (CR) and Peak Signal to Noise Ratio (PSNR), is further improved by utilizing image dependent, variable and non-uniform image sub-blocks generated using a proposed histogram-based merging technique. Experimental results indicate that the proposed linear CSF based quantization technique yields, on an average, 8% increase in CR for the same reconstructed image quality in terms of PSNR as compared to the conventional YCbCr color space. The proposed scheme also outperforms JPEG in terms of CR by an average of 45.01% for the same reconstructed image quality.
Keywords
JPEG; Image Compression; CIE $La^*b^*$ Color Space; Contrast sensitivity function; Quantization;
Citations & Related Records
연도 인용수 순위
  • Reference
1 S.-H. Bae and M. Kim, "A novel DCT-based JND model for luminance adaptation effect in DCT frequency," IEEE Signal Process. Lett., vol. 20, no. 9, pp. 893 - 896, September 2013.   DOI
2 S.-H. Bae and M. Kim, "A novel generalized DCT-based JND profile based on an elaborate CM-JND model for variable block-sized transforms in monochrome images," IEEE Trans. Image Process., vol. 23, no. 8, pp. 3227 - 3240, August 2014.   DOI
3 N. A. Abu, F. Ernawan, N. Suryana, "A Generic Psychovisual Error Threshold for the Quantization Table Generation on JPEG Image Compression," in Proc. of 9th Intl. Coll. Signal Process. Appl., pp. 39 - 43, March 8 - 10, 2013.
4 P. A. M. Oliveira, R. S. Oliveira, R. J. Cintra, F. M. Bayer, A. Madanayake, "JPEG quantisation requires bit-shifts only," Electronics Lett., vol. 53, no. 9, pp. 588-590, April 2017.   DOI
5 H.-H. Chen, Y.-W. Huang and J.-J. Ding, "Local prediction based adaptive scanning for JPEG and H. 264/AVC intra coding," in Proc. of IEEE Intl. Conf. Image Process. (ICIP), pp. 1636-1640, September 15 - 18, 2013.
6 M. B. Akhtar, A. M. Qureshi, "Optimized run length coding for jpeg image compression used in space research program of IST," in Proc. of Intl. Conf. Computer Networks Info. Technol. (ICCNIT), pp. 81-85, July 11 - 13, 2011.
7 G. Lakhani, "Modifying JPEG binary arithmetic codec for exploiting inter/intra-block and DCT coefficient sign redundancies," IEEE Trans. Image Process., vol. 22, no. 4, pp. 1326-1339, April 2013.   DOI
8 J.-J. Ding, H.-H. Chen and W.-Y. Wei, "Adaptive Golomb code for joint geometrically distributed data and its application in image coding," IEEE Trans. Circuits Syst. Video Technol., vol. 23, no. 4, pp. 661-670, April 2013.   DOI
9 J. Mitchell, "Digital compression and coding of continuous-tone still images: Requirements and guidelines," ITU-T Recommendation T. 81, 1992.
10 T. Richter, "JPEG on STEROIDS: Common optimization techniques for JPEG image compression," in Proc. of IEEE Intl. Conf. Image Processing (ICIP), pp. 61 - 65, September 25 - 28, 2016.
11 J.-J. Ding, Y.-W. Huang, P.-Y. Lin, S.-C. Pei, H.-H. Chen and Y.-H. Wang, "Two-dimensional orthogonal DCT expansion in trapezoid and triangular blocks and modified JPEG image compression," IEEE Trans. Image Process, vol. 22, no. 9, pp. 3664-3675, September 2013.   DOI
12 S. Makrogiannis, P. Schelkens, S. Folopoulos and J. Cornelis, "Region-oriented compression of color images using fuzzy inference and shape adaptive DCT," in Proc. of IEEE Intl. Conf. Image Processing (ICIP), pp. 478 - 481, October 7 - 10, 2001.
13 J. Wu, Y. Xing, G. Shi and L. Jiao, "Image Compression with downsampled and overlapped transform at low bit rates," in Proc. of IEEE Intl. Conf. Image Processing (ICIP), pp. 29 - 32, November 7 - 10, 2009.
14 G. Fracastoro, F. Verdoja, M. Grangetto and E. Magli, "Superpixel-driven graph transform for image compression," in Proc. of IEEE Intl. Conf. Image Process. (ICIP), pp. 2631 - 2635, September 27 - 30, 2015.
15 M. Gordan, S. Meza, M. Cislariu, B. Orza, A. Vlaicu, D. Capatina and I. Stoian, "A fuzzy logic approach for the fast approximate computation of image transforms from block JPEG DCT coefficients," in Proc. of IEEE Intl. Conf. Automation, Quality and Testing, Robotics (AQTR), pp. 1-6, May 19 - 21, 2016.
16 S. K. Pattanaik and K. K. Mahapatra, "DHT based JPEG image compression using a novel energy quantization method," in Proc. of IEEE Intl. Conf. Industrial Technol. (ICIT), pp. 2827-2832, December 15 - 17, 2006.
17 Z. Wang, S. Simon, Y. Baroud and S. M. Najmabadi, "Visually lossless image compression extension for JPEG based on just-noticeable distortion evaluation," in Proc. of Intl. Conf. Systems, Signals Image Process. (IWSSIP), pp. 237-240, September 10 - 12, 2015.
18 C. Zhang and X. He, "Image compression by learning to minimize the total error," IEEE Trans. Circuits Syst. Video Technol., vol. 23, no. 4, pp. 565-576, April 2013.   DOI
19 Classic Image Processing Library.
20 C. Qin, C.-C. Chang and Y.-P. Chiu, "A novel joint data-hiding and compression scheme based on SMVQ and image inpainting," IEEE Trans. Image Process., vol. 23, no. 3, pp. 969-978, March 2014.   DOI
21 M. W. Marcellin, M. J. Gormish, A. Bilgin and M. P. Boliek, "An overview of JPEG 2000," In Proc. of IEEE Data Compression Conf. (DCC), pp. 523 - 541, March 28 - 30, 2000.
22 G. Sreelekha and P. S. Sathidevi, "An HVS based adaptive quantization scheme for the compression of color images," Digital Signal Process., vol. 20, no. 4, pp. 1129-1149, July 2010.   DOI
23 F. Dufaux, G. J. Sullivan and T. Ebrahimi, "The JPEG XR image coding standard," IEEE Signal Process. Mag., vol. 26, no. 6, November 2009.
24 A. Skodras, C. Christopoulos and T. Ebrahimi, "The JPEG 2000 still image compression standard," IEEE Signal Process. Mag., vol. 18, no. 5, pp. 36 - 58, September 2001.   DOI
25 G. K. Wallace, "The JPEG still picture compression standard," IEEE Trans. Consumer Electronics, vol. 38, no. 1, pp. xviii-xxxiv, February 1992.
26 Y. Jiang and M. S. Pattichis, "JPEG image compression using quantization table optimization based on perceptual image quality assessment," in Proc. of 45th Asilomar Conf. Signals, Systems Computers (ASILOMAR), pp. 225-229, November 6 - 9, 2011.
27 X. Zhang, S. Wang, K. Gu, W. Lin, S. Ma and W. Gao, "Just-Noticeable Difference-Based Perceptual Optimization for JPEG Compression," IEEE Signal Process. Lett., vol. 24, no. 1, pp. 96-100, January 2017.   DOI
28 J. M. Pascual, H. M. Mora, A. F. Guillo and J. A. Lopez, "Adjustable compression method for still JPEG images," Signal Processing: Image Communication, vol. 32, pp. 16-32, March 2015.   DOI
29 C. Poynton, "Color in digital cinema," C. Swartz (ed.) Understanding Digital Cinema: A Professional Handbook, Elsevier, pp. 57-82, 2005.
30 D. Santa-Cruz and T. Ebrahimi, "A study of JPEG 2000 still image coding versus other standards," in Proc. of 10th European Signal Process. Conf., pp. 1 - 4, September 4 - 8, 2000.
31 Image Databases - Image Processing Place.
32 H. R. Sheikh, M. F. Sabir and A. C. Bovik, "A statistical evaluation of recent full reference quality assessment algorithms," IEEE Trans. Image Process., vol. 15, no. 11, pp. 3440 - 3451, November 2006.   DOI
33 V. Hosu, F. Hahn, O. Wiedemann, S.-H. Jung and D. Saupe, "Saliency driven image coding improves overall percieved JPEG quality," in Proc. IEEE Pic. Coding Symp. (PCS), December 4 - 7, 2016.
34 L. Jin, K. Egiazarian and C.-C. Jay Kuo, "JPEG based perceptual image coding with block based image quality metric," in Proc. of IEEE Intl. Conf. Image Process. (ICIP), pp. 1053-1056, Sept. 30 - Oct. 3, 2012.
35 I. Rhee, G. R. Martin, S. Muthukrishnan and R. A. Packwood, "Quadtree-srtuctured variable-size block-matching motion estimation with minimal error," IEEE Trans. Circuits Syst. Video Technol., vol. 10, no. 1, pp. 42 - 50, February 2000.   DOI
36 T. Nguyen, P. Helle, B. Winken, B. Bross, D. Marpe, H. Schwarz and T. Weigand, "Transform coding techniques in HEVC," IEEE J. Sel. Topics Signal Process., vol. 7, no. 6, pp. 978 - 989, December 2013.   DOI
37 M. Wein, "Variable block-size transforms for H.264," IEEE Trans. Circuits and Syst. Video Technol., vol. 13, no. 7, pp. 604 - 613, July 2003.   DOI
38 T. Huang, S. Dong and Y. Tian, "Representing visual objects in HEVC coding loop," IEEE J. Emerging Sel. Topics Circuits Syst., vol. 4, no. 1, pp. 5 -16, March 2014.   DOI
39 C.-H. Chou and K.-C. Liu, "Colour image compression based on the measure of just noticeable colour difference," IET Image Process., vol. 2, no. 6, pp. 304-322, December 2008.   DOI
40 M. Q. Shaw, J. P. Allebach and E. J. Delp, "Color difference weighted adaptive residual preprocessing using perceptual modeling for video compression," Signal Process.: Image Commun., vol. 39, pp. 355-368, November 2015.   DOI
41 S. A. Klein, A. D. Silverstein and T. Carney, "Relevance of human vision to JPEG-DCT compression," in Proc. of SPIE-The Intl. Soc. Optical Engg., vol. 1666, pp. 200-216, August 1992.
42 E. Dumic, M. Mustra, S. Grgic and G. Gvozden, "Image quality of 4:2:2 and 4:2:0 chroma subsampling formats," in Proc. of Intl. Symp. ELMAR, pp. 19-24, September 28 - 30, 2009.
43 P. Zeng and Z. Chen, "Perceptual quality measure using JND model of the human visual system," in Proc. of Intl. Conf. Electric Info. Control Engg. (ICEICE), pp. 2454-2457, April 15 - 17, 2011.
44 A. Ford and A. Roberts, Colour space conversions, 1998. URL: [Last accessed: 13 December 2007] 2011.
45 X. Zhang, W. Lin and P. Xue, "Improved estimation for just-noticeable visual distortion," Signal Process., vol. 85, no. 4, pp. 795 - 808, January 2005.   DOI
46 R. C. Gonzalez and R. E. Woods, "Digital image processing," 3rd Edition, Prentice Hall, 2002.
47 W. B. Pennebaker and J. L. Mitchell, "JPEG: Still image data compression standard," Springer Science & Business Media, Massachusetts, 1992.
48 G. Lakhani, "Improving DC coding models of JPEG arithmetic coder," IEEE Signal Process. Lett., vol. 11, no. 5, pp. 505-508, May 2004.   DOI
49 A. J. Ahumada and H. A. Peterson, "Luminance-model-based DCT quantization for color image compression," in Proc. of SPIE, Human Vision, Vis. Process. Digital Display III, pp. 365 - 374, August 1992.
50 A. B. Watson, "DCTune: A technique for visual optimization of DCT quantization matrices for individual images," in Proc. of 24th Soc. Info., Display Digital Technol. Papers, pp. 946 - 949, 1993.
51 Z. Wei and K. Ngan, "Spatio-temporal just noticeable distortion profile for grey scale image/video in DCT domain," IEEE Trans. Circuits Syst. Video Technol., vol. 19, no. 3, pp. 337 - 346, February 2009.   DOI
52 L. Ma, K. Ngan, F. Zhang and S. Li, "Adaptive block-size transform based just-noticeable difference model for images/videos," Signal Process.:Image Comm., vol. 26, no. 3, pp. 162 - 174, March 2011.   DOI
53 M. D. Fairchild, Color appearance models, 2nd Edition, John Wiley & Sons, New York, 2013.
54 G. Sharma and R. Bala, "Digital color imaging handbook," CRC press, New York, 2002.
55 I. Hontsch and L. Karam, "Adaptive image coding with perceptual distortion control," IEEE Trans. Image Process., vol. 11, no. 3, pp. 213 - 222, August 2002.   DOI