Underwater Image Enhancement Based on Global and Local Equalization of Histogram and Dual-Image Multi-Scale Fusion
| Autor: | Xipeng Pan, Weidong Zhang, Linfeng Bai, Chenping Zhao |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
General Computer Science
Channel (digital image) multi-scale fusion Computer science media_common.quotation_subject Equalization (audio) ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 02 engineering and technology Image (mathematics) Histogram 0202 electrical engineering electronic engineering information engineering Contrast (vision) pixel intensity center regionalization General Materials Science Computer vision Image restoration media_common business.industry General Engineering 020206 networking & telecommunications Underwater image enhancement Computer Science::Computer Vision and Pattern Recognition histogram equalization 020201 artificial intelligence & image processing Artificial intelligence lcsh:Electrical engineering. Electronics. Nuclear engineering business lcsh:TK1-9971 Image histogram |
| Zdroj: | IEEE Access, Vol 8, Pp 128973-128990 (2020) |
| ISSN: | 2169-3536 |
| Popis: | Underwater images suffer from color cast and low visibility caused by the medium scattering and absorption, which will reduce the use of valuable information from the image. In this paper, we propose a novel method which includes four stages of pixel intensity center regionalization, global equalization of histogram, local equalization of histogram and multi-scale fusion. Additionally, this method uses a pixel intensity center regionalization strategy to perform centralization of the image histogram on the overall image. Global equalization of histogram is employed to correct color of the image according to the characteristics of each channel. Local equalization of dual-interval histogram based on average of peak and mean values is used to improve contrast of the image according to the characteristics of each channel. Dual-image multi-scale fusion to integrate the contrast, saliency and exposure weight maps of the color corrected and contrast enhanced images. Experiments on variety types of degraded underwater images show that the proposed method produces better output results in both qualitative and quantitative analysis, thus, the proposed method outperforms other state-of-the-art methods. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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