Results 31 to 40 of about 14,030 (199)
An improved nonlocal sparse regularization-based image deblurring via novel similarity criteria
International Journal of Advanced Robotic Systems, 2018 Image deblurring is a challenging problem in image processing, which aims to reconstruct an original high-quality image from its blurred measurement caused by various factors, for example, imperfect focusing caused by the imaging system or different ...
Nannan Wang +3 more
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A state-of-the-art review of image motion deblurring techniques in precision agriculture
Heliyon, 2023 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 image information, processing and intelligent decision making, etc.
Yu Huihui, Li Daoliang, Chen Yingyi
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Microscopy Today, 1998 Abstract If you are an optical microscopist, chances are you have sometimes wished for a way to increase the depth of focus of your images. In this article I describe a method that does this using a simple combination of functions built into most image processing software - so it will not cost you very much to try, The method, however ...
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RAID-Net: Region-Aware Image Deblurring Network Under Guidance of the Image Blur Formulation
IEEE Access, 2022 Image deblurring is a challenging field in computational photography and computer vision. In the deep learning era, deblurring methods boosted with neural networks achieve significant results.
Lianjun Liao, Zihao Zhang, Shihong Xia
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COMBINED PATCH-WISE MINIMAL-MAXIMAL PIXELS REGULARIZATION FOR DEBLURRING [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020 Deblurring is a vital image pre-processing procedure to improve the quality of images. It is a classical ill-posed problem. A new blind deblurring method based on image sparsity prior is proposed here.
J. Han, S. L. Zhang, Z. Ye
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Survey on Image Deblurring Algorithms [PDF]
Jisuanji kexueImage deblurring is a classic problem in computer vision,aiming to recover sharp visual information from blurry input images or videos.Blur is often caused by factors such as camera misfocus,camera shake,or fast-moving objects.Traditional deblurring ...
CHEN Kang, LIN Jianhan, LIU Yuanjie
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Image Deblurring Based on Residual Attention and Multi-feature Fusion [PDF]
Jisuanji kexue, 2023 Non-uniform blind deblurring in dynamic scenes is a challenging computer vision problem.Although deblurring algorithms based on deep learning have made great progress,there are still problems such as incomplete deblurring and loss of details.To solve ...
ZHAO Qian, ZHOU Dongming, YANG Hao, WANG Changchen
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Deblurring by Realistic Blurring
, 2020 Existing deep learning methods for image deblurring typically train models using pairs of sharp images and their blurred counterparts. However, synthetically blurring images do not necessarily model the genuine blurring process in real-world scenarios ...
Li, Hongdong +6 more
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Joint Image Deblurring and Matching with Blurred Invariant-Based Sparse Representation Prior
Complexity, 2019 Image matching is important for vision-based navigation. However, most image matching approaches do not consider the degradation of the real world, such as image blur; thus, the performance of image matching often decreases greatly. Recent methods try to
Yuanjie Shao +3 more
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SID: Sensor-Assisted Image Deblurring System for Mobile Devices
IEEE Access, 2019 Handheld mobile photography is often affected by motion blur due to the difficulty of keeping the camera's stable. The existing processing method is usually a high-cost deblurring process of a computer, which seriously affects the user experience, and ...
Qing Wang +4 more
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