TIIS (한국인터넷정보학회)
Current Result Document :
| 한글제목(Korean Title) |
An Adaptive Iterative Algorithm for Motion Deblurring Based on Salient Intensity Prior |
| 영문제목(English Title) |
An Adaptive Iterative Algorithm for Motion Deblurring Based on Salient Intensity Prior |
| 저자(Author) |
Hancheng Yu
Wenkai Wang
Wenshi Fan
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| 원문수록처(Citation) |
VOL 13 NO. 02 PP. 0855 ~ 0870 (2019. 02) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
In this paper, an adaptive iterative algorithm is proposed for motion deblurring by using the salient intensity prior. Based on the observation that the salient intensity of the clear image is sparse, and the salient intensity of the blurred image is less sparse during the image blurring process. The salient intensity prior is proposed to enforce the sparsity of the distribution of the saliency in the latent image, which guides the blind deblurring in various scenarios. Furthermore, an adaptive iteration strategy is proposed to adjust the number of iterations by evaluating the performance of the latent image and the similarity of the estimated blur kernel. The negative influence of overabundant iterations in each scale is effectively restrained in this way. Experiments on publicly available image deblurring datasets demonstrate that the proposed algorithm achieves state-of-the-art deblurring results with small computational costs.
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| 키워드(Keyword) |
Motion deblurring
blind deconvolution
kernel estimation
adaptive iterative strategy
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| 파일첨부 |
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