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• W3048669135 abstract "According to maritime image histograms’ statistic and analysis, the histogram of pure maritime image obeys Gaussian distribution approximately, thus Three Adaptive Sub-histograms Equalization (TASHE) algorithm for maritime image enhancement is proposed in this paper. First, the characteristics of pure maritime image’s histogram are studied, then the adaptive threshold’s optimal selection strategy for the histogram’s division is discussed, finally the implement of three sub-histograms is described. This paper employs visible gray maritime image, visible color maritime image and infrared maritime image to verify the enhancement algorithm’s effectiveness and robustness, the experimental results show that TASHE algorithm can not only keep the maritime image’s mean brightness and naturalness, but also improve the maritime image’s contrast without the noise and artifacts. The objective image quality assessment also indicates that TASHE algorithm can improve the original maritime image’s Enhancement Measure by Entropy (EME) value, furthermore, when a maritime image is pre-processed by TASHE algorithm, the maritime target’s Detection Rate (DR) can be improved." @default.
• W3048669135 created "2020-08-18" @default.
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• W3048669135 date "2020-01-01" @default.
• W3048669135 modified "2023-09-26" @default.
• W3048669135 title "Three Adaptive Sub-Histograms Equalization Algorithm for Maritime Image Enhancement" @default.
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• W3048669135 doi "https://doi.org/10.1109/access.2020.3015839" @default.
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