A Local Brightness Normalization (LBN) algorithm for destriping Hyperion images

M.K. Pal, Alok Porwal

    Research output: Contribution to journalArticlepeer-review

    8 Citations (Scopus)


    © 2015 Taylor & Francis. A hybrid algorithm based on global moments matching and local brightness normalization is proposed for correcting vertical stripes in Hyperion images. Two types of vertical stripes are identified: (1) global stripes comprising entire columns of dark pixels with brightness values lower than the global brightness, and (2) local stripes comprising intermittent segments of pixels within a specific column that have lower brightness values compared with the local neighbourhood brightness. The proposed algorithm operates in four steps. First, a minimum noise fraction-transformation-based filtering is used to minimize spatially decorrelated noise. Then no-data pixels values are corrected. Next, global stripes are demarcated and corrected. Finally, local stripes are flagged and corrected. Applications of the proposed algorithm to two Hyperion datasets show significant reduction in vertical stripes.
    Original languageEnglish
    Pages (from-to)2674-2696
    JournalInternational Journal of Remote Sensing
    Issue number10
    Publication statusPublished - 2015


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