Efficiency analysis of color image filtering

Dmitriy V. Fevralev, Nikolay N. Ponomarenko, Vladimir V. Lukin, Sergey K. Abramov, Karen Egiazarian, Jaakko T. Astola

    Research output: Contribution to journalArticleScientificpeer-review

    40 Citations (Scopus)


    This article addresses under which conditions filtering can visibly improve the image quality. The key points are the following. First, we analyze filtering efficiency for 25 test images, from the color image database TID2008. This database allows assessing filter efficiency for images corrupted by different noise types for several levels of noise variance. Second, the limit of filtering efficiency is determined for independent and identically distributed (i.i.d.) additive noise and compared to the output mean square error of state-of-the-art filters. Third, component-wise and vector denoising is studied, where the latter approach is demonstrated to be more efficient. Fourth, using of modern visual quality metrics, we determine that for which levels of i.i.d. and spatially correlated noise the noise in original images or residual noise and distortions because of filtering in output images are practically invisible. We also demonstrate that it is possible to roughly estimate whether or not the visual quality can clearly be improved by filtering.

    Original languageEnglish
    Article number41
    Number of pages19
    JournalEurasip Journal on Advances in Signal Processing
    Publication statusPublished - 2011
    Publication typeA1 Journal article-refereed


    • image filtering
    • filter efficiency
    • quality metrics
    • color image database
    • DOMAIN
    • SIGNAL
    • NOISE


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