• DocumentCode
    640791
  • Title

    Efficiency of lossy compression of noisy and pre-filtered remote sensing images

  • Author

    Lukin, V.V. ; Zemliachenko, A.N. ; Tchobanou, M.K.

  • Author_Institution
    Dept. of Signal Transm., Nat. Aerosp. Univ., Kharkov, Ukraine
  • fYear
    2013
  • fDate
    23-28 June 2013
  • Firstpage
    343
  • Lastpage
    345
  • Abstract
    This paper state that pre-filtering of noisy image before compression can provide certain benefits only under several conditions. First, a noisy image to be compressed has to have a rather simple structure. Second, noise intensity is to be rather high; only in this case pre-filtering is able to produce considerable improvement of visual quality compared to noisy image. In the case when a pre-filtered image is subject to compression, benefits due to pre-filtering are observed only if compression ratio (quantization step) is not too large. Moreover, we have not observed OOP for pre-filtered and then compressed images. Thus, their quality (according to both standard and HVS-metrics) permanently decrease if compression ratio increases. If CR has to be large, there is no reason to perform pre-filtering of noisy images.
  • Keywords
    data compression; filtering theory; geophysical image processing; image coding; quantisation (signal); remote sensing; HVS-metric; lossy compression; noise intensity; noisy remote sensing images; prefiltered remote sensing images; quantization step; standard metric; visual quality improvement; Hyperspectral sensors; Image coding; Noise; Noise measurement; Standards; Visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Physics and Engineering of Microwaves, Millimeter and Submillimeter Waves (MSMW), 2013 International Kharkov Symposium on
  • Conference_Location
    Kharkiv
  • Print_ISBN
    978-1-4799-1066-3
  • Type

    conf

  • DOI
    10.1109/MSMW.2013.6622050
  • Filename
    6622050