• DocumentCode
    3690738
  • Title

    Compression ratio prediction in lossy compression of noisy images

  • Author

    Alexander N. Zemliachenko;Sergey Abramov;Vladimir V. Lukin;Benoît Vozel;Kacem Chehdi

  • Author_Institution
    National Aerospace University, 61070, Kharkov, Ukraine
  • fYear
    2015
  • fDate
    7/1/2015 12:00:00 AM
  • Firstpage
    3497
  • Lastpage
    3500
  • Abstract
    Our paper addresses a question of prediction compression ratio in lossy compression of remote sensing images by coders based on discrete cosine transform (DCT) taking into account noise present in these images. Quantization step is set fixed and proportional to noise standard deviation to provide compression in optimal operation point if it exists. Simple statistics of DCT coefficients is used for predicting compression ratio. Prediction dependences are obtained offline (in advance) and they occur to be quite simple and accurate. The influence of DCT statistics on prediction efficiency is analyzed. Accuracy of prediction is studied for real-life hyperspectral data compressed component-wise.
  • Keywords
    "Image coding","Discrete cosine transforms","Noise measurement","Standards","Hyperspectral imaging","Fitting"
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2015 IEEE International
  • ISSN
    2153-6996
  • Electronic_ISBN
    2153-7003
  • Type

    conf

  • DOI
    10.1109/IGARSS.2015.7326574
  • Filename
    7326574