Results 21 to 30 of about 14,030 (199)
Guided Image Deblurring by Deep Multi-Modal Image Fusion
IEEE Access, 2022 Estimating sharp images from blurry observations is still a difficult task in the image processing research field. Previous works may produce deblurred images that lose details or contain artifacts.
Yuqi Liu, Zehua Sheng, Hui-Liang Shen
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Sensors, 2021 Complex marine environment has an adverse effect on the object detection algorithm based on the vision sensor for the smart ship sailing at sea. In order to eliminate the motion blur in the images during the navigation of the smart ship and ensure safety,
Hui Feng +3 more
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Blind Deblurring Based on Sigmoid Function
Sensors, 2021 Blind image deblurring, also known as blind image deconvolution, is a long-standing challenge in the field of image processing and low-level vision. To restore a clear version of a severely degraded image, this paper proposes a blind deblurring algorithm
Shuhan Sun +3 more
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Separable Kernel for Image Deblurring [PDF]
2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014 In this paper, we deal with the image deblurring problem in a completely new perspective by proposing separable kernel to represent the inherent properties of the camera and scene system. Specifically, we decompose a blur kernel into three individual descriptors (trajectory, intensity and point spread function) so that they can be optimized separately.
Lu Fang 0001 +4 more
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Learning Wavefront Coding for Extended Depth of Field Imaging [PDF]
, 2020 Depth of field is an important factor of imaging systems that highly affects the quality of the acquired spatial information. Extended depth of field (EDoF) imaging is a challenging ill-posed problem and has been extensively addressed in the literature ...
Akpinar, Ugur +4 more
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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
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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
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A Single Image Deblurring Approach Based on a Fractional Order Dark Channel Prior
International Journal of Applied Mathematics and Computer Science, 2022 The dark channel prior has been successfully applied to solve the blind deblurring problem on different scene images. Since the dark channel of the blurry-noise image is similar to that of the corresponding clear image, the sparsity of the dark channel ...
Yu Xiaoyuan, Xie Wei, Yu Jinwei
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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
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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.
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