摘要
水下拍摄的图像受到悬浮颗粒物散射作用的影响,有可能出现模糊、对比度低、色彩失真等不利情况,影响了图像质量。为了利用人工智能技术增强水下图像的视觉效果,研究过程提出了双重残差混合注意力机制,并在此基础上建立了相应的图像增强算法模型。利用开源数据集检验该算法模型的性能,为其设置四种对照算法。结果显示,其在结构相似性、峰值信噪比两个评价指标上表现最佳,达到了预期目标。
The images taken underwater are affected by the scattering of suspended particles,and may have adverse conditions such as blur,low contrast and color distortion,which affect the image quality.In order to enhance the visual effect of underwater im⁃ages with artificial intelligence technology,the research process proposes the dual residual mixed attention mechanism,and estab⁃lishes the corresponding image enhancement algorithm model on this basis.The use of the open source data set was used to test the performance of the algorithm model,and four control algorithms were set for it.The results showed that the algorithm performed the best in the two evaluation indexes of structural similarity and peak signal⁃to⁃noise ratio,and achieved the expected goal.
作者
李然
Li Ran(School of Information Engineering,Shanxi University of Media and Communication,Jinzhong 030619,China)
出处
《现代计算机》
2024年第17期73-76,共4页
Modern Computer
关键词
双重残差混合注意力网络模型
水下图像增强算法
性能试验
dual residual hybrid attention network model
underwater image enhancement algorithm
performance test
