An Effective Image Enhancement Method for Electronic Portal Images

Mao-Hsiung Hung, S-C Chu, John Roddick, Jeng-Shyang Pan, C-S Shieh

    Research output: Contribution to conferencePaper

    2 Citations (Scopus)

    Abstract

    Due to the inherent low-contrast in Electronic Portal Images (EPI), the perception quality of EPI has certain gap to the expectation of most physicians. It is essential to have effective post-processing methods to enhance the visual quality of EPI. However, only limited efforts had been paid to this issue in the past decade. To this problem, an integrated approach featuring automatic thresholding is developed and presented in this article. Firstly, Gray-Level Grouping (GLG) is applied to improve the global contrast of the whole image. Secondly, Adaptive Image Contrast Enhancement (AICE) is used to refine the local contrast within a neighborhood. Finally, a simple spatial filter is employed to reduce noises. The experimental results indicate that the proposed method greatly improves the visual perceptibility as compared with previous approaches.

    Original languageEnglish
    Pages174-183
    Number of pages10
    DOIs
    Publication statusPublished - 3 Dec 2010
    Event2nd International Conference on Computational Collective Intelligence - Semantic Web, Social Networks & Multiagent Systems - ICCCI 2010 -
    Duration: 10 Nov 2010 → …

    Conference

    Conference2nd International Conference on Computational Collective Intelligence - Semantic Web, Social Networks & Multiagent Systems - ICCCI 2010
    Period10/11/10 → …

    Keywords

    • Adaptive image contrast enhancement
    • Contrast enhancement
    • Electronic portal image
    • Gray-level grouping

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  • Cite this

    Hung, M-H., Chu, S-C., Roddick, J., Pan, J-S., & Shieh, C-S. (2010). An Effective Image Enhancement Method for Electronic Portal Images. 174-183. Paper presented at 2nd International Conference on Computational Collective Intelligence - Semantic Web, Social Networks & Multiagent Systems - ICCCI 2010, . https://doi.org/10.1007/978-3-642-16696-9_19