Results 21 to 30 of about 13,900 (206)
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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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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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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Edge-aware deep image deblurring
Neurocomputing, 2022 Image deblurring is a fundamental and challenging low-level vision problem. Previous vision research indicates that edge structure in natural scenes is one of the most important factors to estimate the abilities of human visual perception. In this paper, we resort to human visual demands of sharp edges and propose a two-phase edge-aware deep network to
Fu, Zhichao +5 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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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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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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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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