• DocumentCode
    3149966
  • Title

    Recompressing images to improve image retrieval performance

  • Author

    Edmundson, David ; Schaefer, Gerald

  • Author_Institution
    Dept. of Comput. Sci., Loughborough Univ., Loughborough, UK
  • fYear
    2012
  • fDate
    25-30 March 2012
  • Firstpage
    1541
  • Lastpage
    1544
  • Abstract
    Virtually all images are stored in compressed form, most in (lossy) JPEG format. Compressing images however has been shown to cause a small but not negligible drop in performance for content-based image retrieval (CBIR) algorithms. In this paper, we show that it is possible to reverse this performance drop. We achieve this by what might at a first glance seem counter-intuitive, namely by compressing the images even more. In detail, what we perform is recompressing images (or rather re-quantising the DCT coefficients) to their lowest common image quality setting. We demonstrate, on a benchmark image retrieval database and using standard CBIR algorithms, that this results in improved image retrieval performance rivalling that of running the algorithms on uncompressed data.
  • Keywords
    data compression; discrete cosine transforms; image coding; image retrieval; CBIR algorithms; DCT coefficients; JPEG format; content-based image retrieval algorithms; image quality setting; image recompression; Discrete cosine transforms; Image coding; Image color analysis; Image retrieval; Q factor; Quantization; Transform coding; Content-based image retrieval; JPEG; image compression; retrieval performance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on
  • Conference_Location
    Kyoto
  • ISSN
    1520-6149
  • Print_ISBN
    978-1-4673-0045-2
  • Electronic_ISBN
    1520-6149
  • Type

    conf

  • DOI
    10.1109/ICASSP.2012.6288185
  • Filename
    6288185