基于感知先验与分量增强的高动态成像方法
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作者单位:

辽宁工程技术大学电信学院

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中图分类号:

TP391.41

基金项目:

国家自然科学基金项目(面上项目,重点项目,重大项目)


High dynamic imaging method based on color a priori and component enhancement
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Affiliation:

1.School of Electronics & Information Engineering;2.School of Electronics and Information Engineering

Fund Project:

The National High Technology Research and Development Program of China (863 Program);The National Natural Science Foundation of China (General Program, Key Program, Major Research Plan)

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    摘要:

    高动态范围成像方法大多存在融合图像亮度不均衡、纹理丢失以及色彩失真等问题。针对此问题,提出了一种基于感知先验与分量增强的高动态成像方法。根据感知先验对多曝光图像分别进行图像增强,保留更多的纹理信息以及色彩真实感;引入注意力门控机制和特征提取操作对亮度分量进行增强;通过联合编码器-解码器网络对色度分量进行增强。对增强后的亮度分量和色度分量进行融合得到最终的融合图像。实验数据选用包含多种复杂场景的多曝光图像序列,结果表明,本文方法在视觉信息保真度达到了0.8268,多曝光融合结构相似度达到了0.9476。本文方法相较于其他方法得到的融合图像,细节更加清晰、图像信息丰富、更符合人眼的视觉感知,融合效果更好。

    Abstract:

    Most high dynamic range imaging methods suffer from uneven brightness, texture loss, and color distortion in the fused images. To address this problem, a high dynamic imaging method based on perceptual a priori and component enhancement is proposed. Based on the perceptual prior, image enhancement is performed on multi-exposure images to retain more texture information and color realism; the luminance component is enhanced by introducing an attention-gating mechanism and a feature extraction operation, and a joint encoder-decoder network enhances the chrominance component. The improved luminance and chrominance components are fused to obtain the final combined image. The experimental data are selected from a sequence of multi-exposure images containing a variety of complex scenes, and the results show that this paper's method achieves a visual information fidelity of 0.8268 and a multi-exposure fusion structure similarity of 0.9476. Compared with the fusion images obtained by other methods, the details of this paper's approach are more precise, the image information is more affluent, it is more in line with the human eye's visual perception, and the fusion effect is better.

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历史
  • 收稿日期:2023-05-10
  • 最后修改日期:2023-07-27
  • 录用日期:2023-08-08
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