Results 101 to 110 of about 946,624 (201)
Deblur-Cyclegan: A Generative Cyclic Approach for Image Blind Motion Deblurring
, 2022 In this paper, we propose an end-to-end generative adversarial network (GAN) for single image blind motion deblur-ring, which we called Deblur-CycleGAN.
Ali Syed Saqlain +9 more
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WRA-Net: Wide Receptive Field Attention Network for Motion Deblurring in Crop and Weed Image. [PDF]
Plant Phenomics, 2023 Yun C, Kim YH, Lee SJ, Im SJ, Park KR.
europepmc +1 more source
Image Motion Deblurring Based on Deep Residual Shrinkage and Generative Adversarial Networks. [PDF]
Comput Intell Neurosci, 2022 Jiang W, Liu A.
europepmc +1 more source
A Neural Approach to Blind Motion Deblurring [PDF]
, 2016 We present a new method for blind motion deblurring that uses a neural network trained to compute estimates of sharp image patches from observations that are blurred by an unknown motion kernel. Instead of regressing directly to patch intensities, this network learns to predict the complex Fourier coefficients of a deconvolution filter to be applied to
openaire +3 more sources
Aided Blind Deblurring Image Degraded by Motion Blur
, 2017 Blur effect is a common phenomenon in photographs when relative motion between a camera and the captured scene occurs during the exposure time. It significantly degrades image quality and has great effect on the performance of subsequent applications ...
Ruiwen Zhen (17549757)
core +1 more source
Depth-Aware Motion Deblurring Using Loopy Belief Propagation
, 2020 Most motion-blurred images captured in the real world have spatially-varying point-spread functions, and some are caused by different positions and depth values, which cannot be handled by most state-of-the-art deblurring methods based on deconvolution ...
Wu, Enhua +4 more
core +1 more source
Infrared video motion deblurring algorithm based on optical flow and sparse attention
Meikuang AnquanThe underground coal mine working environment is characterized by complex spatial structures and significant factors such as widespread equipment vibration. These unique conditions pose severe challenges to the quality of infrared video.
Tianxin BAI +4 more
doaj +1 more source
An Effective Motion Deblurring Method with Sound Extendability
, 2016 Motion Deblurring is a foundational and challenging problem in the community of image and signal processing, has been hotly discussed in recent years. This paper proposes a novel approach to restore motion blurred images using a piecewise function that ...
Wei Ji +5 more
core +1 more source
Gyroscope-aided motion deblurring with deep networks [PDF]
, 2019 We propose a deblurring method that incorporates gyroscope measurements into a convolutional neural network (CNN). With the help of such measurements, it can handle extremely strong and spatially-variant motion blur.
Simo Sarkka +14 more
core +1 more source
Gyroscope-Assisted Motion Deblurring Network
CoRRImage research has shown substantial attention in deblurring networks in recent years. Yet, their practical usage in real-world deblurring, especially motion blur, remains limited due to the lack of pixel-aligned training triplets (background, blurred image, and blur heat map) and restricted information inherent in blurred images. This paper presents a
Simin Luan +6 more
openaire +3 more sources