Results 31 to 40 of about 9,140,641 (221)
Pixel Crosstalk and Correlation with Modulation Transfer Function of CMOS Image Sensor [PDF]
, 2005 The Modulation Transfer Function is a common metric used to quantify image quality but inter-pixel crosstalk analysis is also of interest. Because of an important number of parameters influencing MTF, its analytical calculation and crosstalk ...
Magali Estribeau +3 more
core +1 more source
Blind Image Deblurring Based on Local Edges Selection
Applied Sciences, 2019 The edges of images are less sparse when images become blurred. Selecting effective image edges is a vital step in image deblurring, which can help us to build image deblurring models more accurately.
Yue Han, Jiangming Kan
doaj +1 more source
A Motion Deblur Method Based on Multi-Scale High Frequency Residual Image Learning
IEEE Access, 2020 Non-uniform blind deblurring of dynamic scenes has always been a challenging problem in image processing because of the diverse of blurring sources. Traditional methods based on energy minimization cannot make accurate kernel estimation. It leads to that
Keng-Hao Liu +3 more
doaj +1 more source
Infrared Image Deblurring Based on Generative Adversarial Networks
International Journal of Optics, 2021 Blind deblurring of a single infrared image is a challenging computer vision problem. Because the blur is not only caused by the motion of different objects but also by the relative motion and jitter of cameras, there is a change of scene depth.
Yuqing Zhao +4 more
doaj +1 more source
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
doaj +1 more source
Blind deblurring of natural images [PDF]
2008 IEEE International Conference on Acoustics, Speech and Signal Processing, 2008 A new method to perform blind image deblurring is proposed. Very few assumptions are made on the blurring filter and on the original image: the blurring filter is assumed to have limited support and the original image is assumed to be a sharp natural image. A new prior is used, which gives higher probability to images with sharp edges.
Mariana S. C. Almeida, Luís B. Almeida
openaire +1 more source
Adaptive Single Image Deblurring
CoRR, 2022 This paper tackles the problem of dynamic scene deblurring. Although end-to-end fully convolutional designs have recently advanced the state-of-the-art in non-uniform motion deblurring, their performance-complexity trade-off is still sub-optimal.
Maitreya Suin +2 more
openaire +3 more sources
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
doaj +1 more source
CoRR, 2023 In recent years, deep generative models, such as Generative Adversarial Network (GAN), has grabbed significant attention in the field of computer vision. This project focuses on the application of GAN in image deblurring with the aim of generating clearer images from blurry inputs caused by factors such as motion blur.
openaire +3 more sources
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
doaj +1 more source