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Blur Kernel Optimization: A New Approach to Patch Selection with Adaptive Kernel Estimation
Applied Mechanics and Materials, 2013Recently, many effective approaches appeared in the field of blind image deconvolution to reduce the computational cost. Using multiple smaller regions instead of whole image not only make the restoration efficient but also improves the results by discarding the ineffectual regions. It is observed that a study is needed to compare different methods for
Saqib Yousaf, Shi Yin Qin
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Blur Kernel Estimation Model with Combined Constraints for Blind Image Deblurring
2018 Digital Image Computing: Techniques and Applications (DICTA), 2018This paper proposes a blur kernel estimation model based on combined constraints involving both image and blur kernel constraints for blind image deblurring. We adopt L0 regularization term for constraining image gradient and dark channel of image gradient to protect image strong edges and suppress noise in image, and use L2 regularization term as ...
Ying Liao +3 more
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5th International Conference on Computer Sciences and Convergence Information Technology, 2010
Optical flow methods, such as Lucas-Kanade and Horn-Schunck algorithms, are popular in motion estimation. However, they fall short on accuracy when they are applied to blurred videos. Some people utilize hybrid camera system to get a low resolution image to suppress the blurring effect so that more accurate optical flow for blurred high resolution ...
Luo, T +5 more
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Optical flow methods, such as Lucas-Kanade and Horn-Schunck algorithms, are popular in motion estimation. However, they fall short on accuracy when they are applied to blurred videos. Some people utilize hybrid camera system to get a low resolution image to suppress the blurring effect so that more accurate optical flow for blurred high resolution ...
Luo, T +5 more
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Acoustic blur kernel with sliding window for blind estimation of reverberation time
2015 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), 2015Reverberation time, or T 60 , is a key parameter used for characterizing acoustic spaces. Blind T 60 estimation is useful for many applications including speech intelligibility estimation, acoustic scene analysis and dereverberation. In our previous work, a single-channel blind T 60 estimator was proposed employing spectral analysis in the modulation
Felicia Lim +3 more
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Spatial-scale-regularized blur kernel estimation for blind image deblurring
Signal Processing: Image Communication, 2018Abstract Blind image deblurring is a long-standing and challenging inverse problem in image processing. In this paper, we propose a new spatial-scale-regularized approach to estimate a blur kernel (BK) from a single motion blurred image by regularizing the spatial scale sizes of image edges.
Shu Tang +5 more
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Motion blur kernel estimation in steerable gradient domain of decomposed image
Multidimensional Systems and Signal Processing, 2015zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kai Wang, Liang Xiao 0001, Zhihui Wei
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Event-based Blur Kernel Estimation For Blind Motion Deblurring
2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2023Takuya Nakabayashi +3 more
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Deep Kernel Estimation for Turbulent Blur Correction
2023 IEEE 5th International Conference on Civil Aviation Safety and Information Technology (ICCASIT), 2023openaire +1 more source
Blur kernel estimation using sparsity and local smoothness prior
Journal of Electronic Imaging, 2017Bo Dong +3 more
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