Results 81 to 90 of about 12,142,372 (124)

Data-driven gradient priors integrated into blind image deblurring

Blind image deblurring is a severely ill-posed task. Most existing methods focus on deep learning to learn massive data features while ignoring the vital significance of classic image structure priors.
Li, Chongyi, Guo, Jichang, Qing, Qi
core   +1 more source

Patch-Wise Blind Image Deblurring Via Michelson Channel Prior

IEEE Access, 2019
Motion blur exists in many computer vision tasks, including faces, texts, and low-illumination images etc. It has been proved that Dark Channel Prior (DCP) and Bright Channel Prior (BCP) can both help the image deblurring by enhancing the dark or bright ...
Guoquan Wen, Chao Min, Zeyun Jiang, Zhaozhong Yang, Xiaogang Li   +4 more
doaj   +1 more source

Blind UAV Images Deblurring Based on Discriminative Networks

Sensors, 2018
Unmanned aerial vehicles (UAVs) have become an important technology for acquiring high-resolution remote sensing images. Because most space optical imaging systems of UAVs work in environments affected by vibrations, the optical axis motion and image ...
Ruihua Wang, Guorui Ma, Qianqing Qin, Qiang Shi, Juntao Huang   +4 more
doaj   +1 more source

A Novel Fractional-Order Non-Convex TV^α,p Model in Image Deblurring

Fractal and Fractional
In this paper, we propose a non-convex model with fractional-order applied to image deblurring problems. In the new model, fractional-order gradients have been introduced to preserve detailed features, and a source term with a blurry kernel is used for ...
Bao Chen, Xiaohua Ding, Yuchao Tang
doaj   +1 more source

Dynamic Image Deblurring based on Crosshatch Attention Adversarial Network and Hybrid Loss

Image deblurring techniques that uses deep learning have shown great potential but due to low generalizability, noise immunity and the correlation among different pixels is not addressed in detail that results in unwanted artifact that appears in the ...
Shaukat, A, Azam, B, Aslam, U
core   +1 more source

An Edge-Enhanced Branch for Multi-Frame Motion Deblurring

IEEE Access
Non-uniform deblurring is one of the most important image restoration tasks for providing appropriate information for subsequent applications that require image recognition.
Sota Moriyama, Koichi Ichige
doaj   +1 more source

Residual Diffusion Deblurring Model for Single Image Defocus Deblurring

Defocus deblurring is a challenging task due to the spatially varying nature of defocus blur with multiple plausible solutions of a single given image.
Zhou, Haohui, Zhu, Lei, Chen, Sixiang, Feng, Haoxuan, Ye, Tian   +4 more
core   +1 more source

Image Deblurring and Effect of Wiener, Regularized, Lucky-Richardson, Blind-Deconvolution, Average and Median Filters on Blurred Image and Noisy Image

Tikrit Journal of Engineering Sciences, 2014
In image deblurring, we try to recover the original, sharp image by using a mathematical model of the blurring process. There are several techniques to recover the original image, but they could not recover the image exactly.
Shayma Wail Nourildean Mohammed Ismaeel Khalil
doaj  

Image deblurring by multi-scale modified U-Net using dilated convolution

Science Progress
In 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, Song-Yih Lin, Min-Lang Yang, Chung-Chi Huang, Jen-Chun Lee   +4 more
doaj   +1 more source

Uncertainty Propagation in Image Deblurring [PDF]

Image blur often hinders radiographic data analysis. By approaching image deblurring as an ill-posed inverse problem, methods such as Tikhonov and Total Variation Regularization provide ample solutions. As non-blind methods, the regularization requires a
Sigel, Eleanor, Gorman, Madeline, Pasfield, Thomas   +2 more
core   +1 more source