An image defocus deblurring method based on gradient difference of boundary neighborhood

Q1 Computer Science Virtual Reality Intelligent Hardware Pub Date : 2023-12-01 DOI:10.1016/j.vrih.2023.06.008
Junjie TAO , Yinghui WANG , Haomiao M.A , Tao YAN , Lingyu AI , Shaojie ZHANG , Wei LI
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Abstract

Background

For static scenes with multiple depth layers, the existing defocused image deblurring methods have the problems of edge ringing artifacts or insufficient deblurring degree due to inaccurate estimation of blur amount, In addition, the prior knowledge in non blind deconvolution is not strong, which leads to image detail recovery challenge.

Methods

To this end, this paper proposes a blur map estimation method for defocused images based on the gradient difference of the boundary neighborhood, which uses the gradient difference of the boundary neighborhood to accurately obtain the amount of blurring, thus preventing boundary ringing artifacts. Then, the obtained blur map is used for blur detection to determine whether the image needs to be deblurred, thereby improving the efficiency of deblurring without manual intervention and judgment. Finally, a non blind deconvolution algorithm is designed to achieve image deblurring based on the blur amount selection strategy and sparse prior.

Results

Experimental results show that our method improves PSNR and SSIM by an average of 4.6% and 7.3%, respectively, compared to existing methods.

Conclusions

Experimental results show that our method outperforms existing methods. Compared with existing methods, our method can better solve the problems of boundary ringing artifacts and detail information preservation in defocused image deblurring.

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基于边界邻域梯度差的图像散焦去模糊方法
背景对于具有多个深度层的静态场景,现有的虚焦图像去模糊方法存在边缘振铃伪影或由于模糊量估计不准确导致去模糊程度不够的问题,此外,非盲去卷积中的先验知识不强,导致图像细节恢复面临挑战。方法为此,本文提出了一种基于边界邻域梯度差的失焦图像模糊图估计方法,该方法利用边界邻域梯度差来准确获取模糊量,从而防止边界振铃伪影。然后,利用获得的模糊图进行模糊检测,以确定图像是否需要去模糊,从而提高去模糊的效率,无需人工干预和判断。最后,基于模糊量选择策略和稀疏先验,设计了一种非盲解卷积算法来实现图像去模糊。结果实验结果表明,与现有方法相比,我们的方法平均提高了 4.6% 的 PSNR 和 7.3% 的 SSIM。实验结果表明,我们的方法优于现有方法。与现有方法相比,我们的方法能更好地解决虚焦图像去模糊中的边界振铃伪影和细节信息保留问题。
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来源期刊
Virtual Reality  Intelligent Hardware
Virtual Reality Intelligent Hardware Computer Science-Computer Graphics and Computer-Aided Design
CiteScore
6.40
自引率
0.00%
发文量
35
审稿时长
12 weeks
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