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Image Deblurring Using Multi-Stream Bottom-Top-Bottom Attention Network and Global Information-Based Fusion and Reconstruction Network [PDF]
Sensors, 2020 Image deblurring has been a challenging ill-posed problem in computer vision. Gaussian blur is a common model for image and signal degradation. The deep learning-based deblurring methods have attracted much attention due to their advantages over the ...
Quan Zhou, Mingyue Ding, Xuming Zhang
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A survey on facial image deblurring
Computational Visual Media, 2023 When a facial image is blurred, it significantly affects high-level vision tasks such as face recognition. The purpose of facial image deblurring is to recover a clear image from a blurry input image, which can improve the recognition accuracy, etc ...
Bingnan Wang, Fanjiang Xu, Quan Zheng
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Deep Lidar-Guided Image Deblurring [PDF]
SensorsThe rise in portable Lidar instruments enables new opportunities for depth-assisted image processing. In this paper, we study whether the depth information provided by mobile Lidar sensors present in recent smartphones is useful for the task of image ...
Ziyao Yi +3 more
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Image deblurring by multi-scale modified U-Net using dilated convolution [PDF]
Science ProgressIn modern urban traffic systems, intersection monitoring systems are used to monitor traffic flows and track vehicles by recognizing license plates. However, intersection monitors often produce motion-blurred images because of the rapid movement of cars.
Xiao-Pei Shi +4 more
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Overview of Blind Deblurring Methods for Single Image [PDF]
Jisuanji kexue yu tansuo, 2022 Image deblurring has been a research hotspot in computer vision and image processing for a long time. The motion blur or focus blur image caused by camera jitter, object motion or defocus will seriously affect the use and follow-up processing of the ...
LIU Liping, SUN Jian, GAO Shiyan
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Gradient-wise search strategy for blind image deblurring [PDF]
MATEC Web of Conferences, 2022 Blind image deblurring is a long-standing challenging problem to improve the sharpness of an image as a prerequisite step. Many iterative methods are widely used for the deblurring image, but care must be taken to ensure that the methods have fast ...
Wang Yunhong, Liu Dan
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Blind Deblurring Based on a Single Luminance Channel and L1-Norm
IEEE Access, 2021 To improve the image quality of the deblurring results restored by existing blind deblurring method, an effective image blind deblurring method based on a single channel and L1-norm is proposed for the blurry images.
Luoyu Zhou, Zhiyang Liu
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MedDeblur: Medical Image Deblurring with Residual Dense Spatial-Asymmetric Attention
Mathematics, 2022 Medical image acquisition devices are susceptible to producing blurry images due to respiratory and patient movement. Despite having a notable impact on such blind-motion deblurring, medical image deblurring is still underexposed.
S. M. A. Sharif +5 more
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Iterative Dual CNNs for Image Deblurring
Mathematics, 2022 Image deblurring attracts research attention in the field of image processing and computer vision. Traditional deblurring methods based on statistical prior largely depend on the selected prior type, which limits their restoring ability.
Jinbin Wang, Ziqi Wang, Aiping Yang
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Reference-Based Multi-Level Features Fusion Deblurring Network for Optical Remote Sensing Images
Remote Sensing, 2022 Blind image deblurring is a long-standing challenge in remote sensing image restoration tasks. It aims to recover a latent sharp image from a blurry image while the blur kernel is unknown.
Zhiyuan Li +4 more
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