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Self-supervised blind motion deblurring with deep expectation maximization
When taking a picture, any camera shake during the shutter time can result in a blurred
image. Recovering a sharp image from the one blurred by camera shake is a challenging …
image. Recovering a sharp image from the one blurred by camera shake is a challenging …
Gaussian kernel mixture network for single image defocus deblurring
Defocus blur is one kind of blur effects often seen in images, which is challenging to remove
due to its spatially variant amount. This paper presents an end-to-end deep learning …
due to its spatially variant amount. This paper presents an end-to-end deep learning …
Deep single image defocus deblurring via gaussian kernel mixture learning
This paper proposes an end-to-end deep learning approach for removing defocus blur from
a single defocused image. Defocus blur is a common issue in digital photography that poses …
a single defocused image. Defocus blur is a common issue in digital photography that poses …
A comprehensive survey on deep neural image deblurring
SA Biyouki, H Hwangbo - arxiv preprint arxiv:2310.04719, 2023 - arxiv.org
Image deblurring tries to eliminate degradation elements of an image causing blurriness
and improve the quality of an image for better texture and object visualization. Traditionally …
and improve the quality of an image for better texture and object visualization. Traditionally …
Prior and prediction inverse kernel transformer for single image defocus deblurring
Defocus blur, due to spatially-varying sizes and shapes, is hard to remove. Existing methods
either are unable to effectively handle irregular defocus blur or fail to generalize well on …
either are unable to effectively handle irregular defocus blur or fail to generalize well on …
Blind deblurring text images via Beltrami regularization
H Gao, M Feng - Image and Vision Computing, 2024 - Elsevier
This article proposes a blind image deblurring model based on Beltrami regularization. The
existence and uniqueness of the Beltrami model are proved, and we perform a theoretical …
existence and uniqueness of the Beltrami model are proved, and we perform a theoretical …
HCTIRdeblur: A hybrid convolution-transformer network for single infrared image deblurring
S Yi, L Li, X Liu, J Li, L Chen - Infrared Physics & Technology, 2023 - Elsevier
Infrared images captured by mobile platforms often suffer image blurs such as defocus blur
and motion blur, which seriously degrade the quality of infrared images. However, the …
and motion blur, which seriously degrade the quality of infrared images. However, the …
A state-of-the-art review of image motion deblurring techniques in precision agriculture
Y Huihui, L Daoliang, C Yingyi - Heliyon, 2023 - cell.com
Image motion deblurring is a crucial technology in computer vision that has gained
significant attention attracted by its outstanding ability for accurate acquisition of motion …
significant attention attracted by its outstanding ability for accurate acquisition of motion …
Lightweight MIMO-WNet for single image deblurring
Single image deblurring, aiming at recovering a latent sharp image from a blurry image, is a
highly ill-posed task as there exist infinite feasible solutions. One successful practice of the …
highly ill-posed task as there exist infinite feasible solutions. One successful practice of the …
SEBR: scharr edge-based regularization method for blind image deblurring
The main objective of blind image deblurring is to restore a high-quality sharp image from a
blurry input through estimation of unknown blur kernel and latent sharp image. This is an ill …
blurry input through estimation of unknown blur kernel and latent sharp image. This is an ill …