基于图像融合的水下桥墩裂纹图像增强方法
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作者:
作者单位:

1.江苏科技大学;2.江苏科技大学机械工程学院;3.浙江省海洋开发研究院

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中图分类号:

TP391.41;S979

基金项目:

浙东跨海大桥水下多元协同检测关键技术及应用示范


Image enhancement method of underwater pier crack based on image fusion
Author:
Affiliation:

1.Jiangsu-University-of-Science-and-Technology;2.School of Mechanical Engineering, Jiangsu University of Science and Technology;3.Zhejiang Marine Development Research Institute

Fund Project:

Key technology and application demonstration of underwater multi-component collaborative detection for East Zhejiang Sea Bridge

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    摘要:

    针对水下桥墩裂纹图像存在模糊、亮度差、对比度低等问题,提出了一种基于图像融合的水下桥墩裂纹图像增强方法。首先利用同态滤波对裂纹图像进行去噪声处理, 去除水下环境对裂纹图像的噪声影响;其次对同态滤波处理后的裂纹图像从红-绿-蓝(Red-Green-Blue,RGB)空间转换为LAB空间,对LAB空间中的L通道利用自适应伽马校正对裂纹图像进行亮度处理, 将处理后的裂纹图像转换回RGB空间得到增强的裂纹图像1;将同态滤波处理后的裂纹图像利用限制对比度自适应直方图均衡化处理得到对比度加强的裂纹图像2;最后将图像1和图像2进行加权融合得到最终的增强图像。应用主观视觉效果和3种客观评价指标来验证本文算法的可靠性,结果表明,本文方法处理的裂纹图像亮度、清晰度、对比度均得到有效提升。

    Abstract:

    In response to issues such as blurriness, low brightness, and poor contrast in underwater bridge pier crack images, this paper proposes an image enhancement method based on image fusion. Firstly, Homomorphic Filtering is applied to denoise the crack images, eliminating the noise impact of the underwater environment. Subsequently, the Homomorphic Filtering processed crack images are transformed from the RGB(Red,Green,Blue) space to the LAB space. The L channel in the LAB space is subjected to adaptive gamma correction for brightness adjustment, and the processed crack images are then converted back to the RGB space, resulting in enhanced crack images (Image 1). The crack images processed by homomorphic filtering are also subjected to contrast enhancement through contrast limited adaptive histgram equalization, producing contrast-enhanced crack images (Image 2). Finally, Image 1 and Image 2 are weighted fused to obtain the ultimate enhanced image. Subjective visual effects and three objective evaluation metrics are employed to validate the reliability of the proposed analysis method. The results indicate that the proposed method effectively enhances the brightness, clarity, and contrast of the crack images processed in this paper.

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  • 收稿日期:2023-09-08
  • 最后修改日期:2023-12-10
  • 录用日期:2023-12-18
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