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An Enhancing Approach for Typhoon Cloud Image

Published: 25 March 2020 Publication History

Abstract

We develop an efficient approach for enhancing the contrast of single typhoon cloud image. We first perform an invert operation on an input image for capturing more detail information. Then we employ a simple but effective modified histogram model to generate the distribution function which enhances the contrast of the inverted image. The final enhanced typhoon cloud image is obtained through inverting the enhanced image. Compared with several enhancement methods, the proposed method achieves better subjective results and objective assessments. Furthermore, our method can provide a fast segmentation of typhoon eye.

References

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    ICIGP '20: Proceedings of the 2020 3rd International Conference on Image and Graphics Processing
    February 2020
    172 pages
    ISBN:9781450377201
    DOI:10.1145/3383812
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    In-Cooperation

    • Nanyang Technological University
    • UNIBO: University of Bologna

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 25 March 2020

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    Author Tags

    1. Typhoon cloud image
    2. contrast enhancement
    3. fast segmentation
    4. image inverse
    5. modified histogram

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    • Research-article
    • Research
    • Refereed limited

    Funding Sources

    • The Startup Foundation for Introducing Talent of NUIST
    • National Natural Science Foundation of China under Grant
    • College Students Practice Innovation Training Program of NUIST

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    ICIGP 2020

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