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作 者:王伟 张思远[2] 刘晓芮 WANG Wei;ZHANG Siyuan;LIU Xiaorui(Department of Basic Teaching,Liaoning Technical University,Liaoning Technical University,Huludao,Liaoning 125105,China;School of Electronic and Information Engineering,Huludao,Liaoning 125105,China)
机构地区:[1]辽宁工程技术大学基础教学部,辽宁葫芦岛125105 [2]辽宁工程技术大学电子与信息工程学院,辽宁葫芦岛125105
出 处:《光电子.激光》2025年第1期36-45,共10页Journal of Optoelectronics·Laser
基 金:国家自然科学基金(61601213);辽宁省教育厅基本科研项目(面上项目)(LJKZ0362)资助项目。
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(perceptual priori,PP)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(feature extraction,FE)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,本文方法的视觉信息保真度达到了0.8268,多曝光融合(multi-exposure fusion,MEF)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。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 priori(PP)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(FE)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(MEF)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.
关 键 词:高动态成像 多曝光图像融合 感知先验(PP) 分量增强
分 类 号:TP391.41[自动化与计算机技术—计算机应用技术]
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