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A No-Reference Adaptive Blockiness Measure for JPEG Compressed Images

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  • Chaoying Tang
  • Biao Wang

Abstract

Digital images have been extensively used in education, research, and entertainment. Many of these images, taken by consumer cameras, are compressed by the JPEG algorithm for effective storage and transmission. Blocking artifact is a well-known problem caused by this algorithm. Effective measurement of blocking artifacts plays an important role in the design, optimization, and evaluation of image compression algorithms. In this paper, we propose a no-reference objective blockiness measure, which is adaptive to high frequency component in an image. Difference of entropies across blocks and variation of block boundary pixel values in edge images are adopted to calculate the blockiness level in areas with low and high frequency component, respectively. Extensive experimental results prove that the proposed measure is effective and stable across a wide variety of images. It is robust to image noise and can be used for real-world image quality monitoring and control. Index Terms—JPEG, no-reference, blockiness measure

Suggested Citation

  • Chaoying Tang & Biao Wang, 2016. "A No-Reference Adaptive Blockiness Measure for JPEG Compressed Images," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-12, November.
    • Handle: RePEc:plo:pone00:0165664
    DOI: 10.1371/journal.pone.0165664
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    Cited by:

    1. Siow Hoo Leong & Seng Huat Ong, 2017. "Similarity measure and domain adaptation in multiple mixture model clustering: An application to image processing," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-30, July.

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