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基于水下成像模型的圖像清晰化算法

楊愛萍,  曲暢,  王建,  張莉云

楊愛萍, 曲暢, 王建, 張莉云. 基于水下成像模型的圖像清晰化算法[J]. 電子與信息學報, 2018, 40(2): 298-305. doi: 10.11999/JEIT170460
引用本文: 楊愛萍, 曲暢, 王建, 張莉云. 基于水下成像模型的圖像清晰化算法[J]. 電子與信息學報, 2018, 40(2): 298-305. doi: 10.11999/JEIT170460
Underwater Image Visibility Restoration Based on Underwater Imaging Model[J]. Journal of Electronics & Information Technology, 2018, 40(2): 298-305. doi: 10.11999/JEIT170460
Citation: Underwater Image Visibility Restoration Based on Underwater Imaging Model[J]. Journal of Electronics & Information Technology, 2018, 40(2): 298-305. doi: 10.11999/JEIT170460

基于水下成像模型的圖像清晰化算法

doi: 10.11999/JEIT170460
  • 1.

    (天津大學電氣自動化與信息工程學院 天津 300072)

基金項目: 

國家自然科學基金(61372145, 61472274)

Underwater Image Visibility Restoration Based on Underwater Imaging Model

Funds: 

The National Natural Science Foundation of China (61372145, 61472274)

  • 摘要: 受水下場景中有機物和懸浮顆粒的影響，水下圖像存在對比度低、顏色失真和細節(jié)丟失等問題。同時，水下場景中通常有人工光源存在，造成圖像光照不均。傳統(tǒng)基于圖像去霧的方法用于水下圖像復原時效果欠佳，為充分考慮水對光的吸收和散射作用，近期提出了新的水下成像模型和圖像復原方法。但是這些方法未考慮紅通道影響，導致估計的散射比偏大；另外，也未考慮人工光源的影響，導致估計的背景光過大。針對這些問題，該文提出一套有效的水下圖像清晰化方案。首先，通過設(shè)置閾值確定是否將紅通道信息用于暗通道計算，并將反映人工光源影響的飽和度指標用于散射比估計，以減小人工光源的影響。由此，提出了基于紅通道預判和飽和度指標的暗通道計算方法。然后，根據(jù)三通道衰減系數(shù)比估計每個通道的透射率，可彌補目前很多方法假設(shè)藍綠通道透射率一致的缺陷。最后，利用Shades of Gray算法估計環(huán)境光，并結(jié)合新的水下成像模型得到復原圖像。實驗結(jié)果表明，該文算法可顯著提升圖像的對比度，得到顏色自然、細節(jié)清晰的復原圖像。
    Abstract: As a result of the existence of organisms and suspended particles under underwater conditions, images captured under water usually have low contrast, color distortion and loss of visibility. At the same time, due to the existence of the artificial light source, the underwater image usually has the non-uniform illumination. Traditional hazy-removal methods perform poorly under water. In order to take both absorption and scattering into consideration, a new underwater image formation model and restoration methods are proposed recently. However, these methods ignore the great impact of the red channel information and artificial light source. To solve this problem, a new approach is proposed for underwater image visibility restoration. Firstly, a threshold is set to determine whether to use the red channel information to estimate the dark channel, and a saturation indicator which is used to indicate the impact of artificial light source is utilized to calculate the scattering rate. Based on the red channel information anticipation and the saturation indicator, a new method is proposed to estimate the dark channel. Then, the transmission of each channel is estimated according to the attenuation coefficient ratio, which makes the proposed method more robust. Finally, the ambient light is obtained using the Shades of Gray algorithm, and the visibility restoration result is achieved based on a new underwater image formation model. Experimental results demonstrate that the proposed algorithm can significantly improve the contrast of the underwater image with more natural color and better visibility.
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  • HUANG Bingjing, LIU Tiegen, HU Haofeng, et al. Underwater image recovery considering polarization effects of objects[J]. Optics Express, 2016, 24(9): 9826-9838. doi: 10.1364/OE.24.009826.
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出版歷程
  • 收稿日期:  2017-05-15
  • 修回日期:  2017-11-02
  • 刊出日期:  2018-02-19

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