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Measuring Blockiness of Videos Using Edge Enhancement Filtering

  • Conference paper
Signal Processing, Image Processing and Pattern Recognition (SIP 2011)

Abstract

To represent high quality videos or images with low bit rate, an effective compression algorithm removes the redundancy because of statistical correlation and also the insignificant component of image signal. This paper represents a new algorithm to measure the blocking artifacts of videos by analyzing the distortions of local properties of image signals like dominant edge magnitude and direction. Extensive experiments on various videos show that the new algorithm is very much efficient and faster to measure the blocking artifacts in real time video error detection applications.

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References

  1. Liu, S., Bovik, A.C.: Efficient DCT-Domain Blind Measurement and Reduction of Blocking Artifacts. IEEE Trans.on CSVT 12(12), 1139–1149 (2002)

    Google Scholar 

  2. Wang, Z., Bovik, A.C., Evan, B.L.: Blind measurement of blocking artifacts in images. In: International Conference on Image Processing, Vancouver, BC, Canada (2000)

    Google Scholar 

  3. Wang, Z., Sheikh, H.R., Bovik, A.C.: No-Reference Perceptual Quality Assessment of JPEG Compressed Images. In: IEEE International Conference on Image Processing, pp. 477–480 (2002)

    Google Scholar 

  4. Tan, K.T., Ghanbari, M.: Frequency domain measurement of blockiness in MPEG- 2 coded video. In: International Conference on Image Processing, Vancouver, BC, Canada (2000)

    Google Scholar 

  5. Wu, H.R., Yuen, M.: A generalized block-edge impairment metric for video coding. IEEE Signal Processing Letters 4(11), 317–320 (1997)

    Article  Google Scholar 

  6. Muijs, R., Kirenko, I.: A no-reference blocking artifact measure for adaptive video processing. In: European Signal Processing Conference, Antalya, Turkey (2005)

    Google Scholar 

  7. Chou, C., Li, L.: A perceptually tuned subband image coder based on the measure of just-noticeable-distortion profile. IEEE Trans.on CSVT 5(6), 467–476 (1995)

    Google Scholar 

  8. Karunasekera, S.A., Kingsbury, N.G.: A Distortion Measure for Blocking Artifacts in Images Based on Human Visual Sensitivity. IEEE Transactions on Image Processing 4(6), 713–724 (1995)

    Article  Google Scholar 

  9. Liu, H., Heynderickx, I.: A no-reference perceptual blockiness metric. In: International Conference on Acoustics, Speech, and Signal Processing, Las Vegas, NV, USA (2008)

    Google Scholar 

  10. Yu, Z., Wu, H.R., Winkler, S., Chen, T.: Vision-Model-Based Impairment Metric to Evaluate Blocking Artifacts in Digital Video. Proceedings of the IEEE 90, 154–169 (2002)

    Article  Google Scholar 

  11. Sheikh, H.R., Wang, Z., Cormack, L., Bovik, A.C.: LIVE image quality assessment database release 2 (2005), http://live.ece.utexass.edu/research/quality

  12. Sheikh, H.R., Sabir, M.F., Bovik, A.C.: A statistical evaluation of recent full reference image quality assessment algorithms. IEEE Transactions on Image Processing 15(11), 3440–3451 (2006)

    Article  Google Scholar 

  13. Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: Image quality assessment: from error visibility to structural similarity. IEEE Transactions on Image Processing 13(4), 600–612 (2004)

    Article  Google Scholar 

  14. Seshadrinathan, K., Soundararajan, R., Bovik, A.C., Cormack, L.K.: Study of subjective and objective quality assessment of video. IEEE Transactions on Image Processing 9(6), 1427–1441 (2010)

    Article  MathSciNet  Google Scholar 

  15. Seshadrinathan, K., Soundararajan, R., Bovik, A.C., Cormack, L.K.: A subjective study to evaluate video quality assessment algorithms. In: SPIE Proceedings Human Vision and Electronic Imaging (2010)

    Google Scholar 

  16. Baroncini, V.: ISO/IEC JTC 1/SC29/WG 11, 4240, Sidney (2001)

    Google Scholar 

  17. VQEG: Final report from the video quality experts group on the validation of objective quality metrics for video quality assessment, http://www.its.bldrdoc.gov/vqeg/projects/frtv_phaseI

  18. Vlachos, T.: Detection of blocking artifacts in compressed video. IET Electronics Letters 36(13), 1106–1108 (2000)

    Article  Google Scholar 

  19. Pan, F., Lin, X., Rahardja, S., Lin, W., Ong, E., Yao, S., Lu, Z., Yang, X.: A locally-adaptive algorithm for measuring blocking artifacts in images and videos. In: International Symposium on Circuits and Systems, Vancouver, BC, Canada (2004)

    Google Scholar 

  20. Perra, C., Massidda, F., Giusto, D.D.: Image blockiness evaluation based on Sobel operator. In: International Conference on Image Processing, Genova, Italy (2005)

    Google Scholar 

  21. Pan, F., Lin, X., Rahardja, S., Ong, E.P., Lin, W.S.: Using edge direction information for measuring blocking artifacts of images. Multidimensional Systems and Signal Processing 18(4), 279–308 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  22. Pratt, W.K.: Digital Image Processing. Wiley, New York (1978)

    MATH  Google Scholar 

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© 2011 Springer-Verlag Berlin Heidelberg

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Hasan, M.M., Ahn, K., Chae, O. (2011). Measuring Blockiness of Videos Using Edge Enhancement Filtering. In: Kim, Th., Adeli, H., Ramos, C., Kang, BH. (eds) Signal Processing, Image Processing and Pattern Recognition. SIP 2011. Communications in Computer and Information Science, vol 260. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27183-0_2

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  • DOI: https://doi.org/10.1007/978-3-642-27183-0_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-27182-3

  • Online ISBN: 978-3-642-27183-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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