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International Conference on Signal Processing, Image Processing, and Pattern Recognition

SIP 2011: Signal Processing, Image Processing and Pattern Recognition pp 10–19Cite as

Measuring Blockiness of Videos Using Edge Enhancement Filtering

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 260))

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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Author information

Authors and Affiliations

  1. Image Processing Lab, Department of Computer Engineering, Kyung Hee University, South Korea

    Md. Mehedi Hasan, Kiok Ahn & Oksam Chae

Authors
  1. Md. Mehedi Hasan
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  2. Kiok Ahn
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  3. Oksam Chae
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Editor information

Editors and Affiliations

  1. Multimedia Engineering Department, Hannam University, 133 Ojeong-dong, Daeduk-gu, Daejeon, Korea

    Tai-hoon Kim

  2. The Ohio State University, 470 Hitchcock Hall, 2070 Neil Avenue, 43210-1275, Columbus, OH, USA

    Hojjat Adeli

  3. University of Porto, 4099-002, Porto, Portugal

    Carlos Ramos

  4. School of Computing and Information Systems, University of Tasmania, Hobart, TAS, Australia

    Byeong-Ho Kang

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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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