Results 91 to 100 of about 13,900 (206)
Blind and Non-Blind Deconvolution-Based Image Deblurring Techniques for Blurred and Noisy Image
Tikrit Journal of Engineering Sciences: Image deblurring is a common issue in low-level computer vision aiming to restore a clear image from a blurred input image. Deep learning innovations have significantly advanced the solution to this issue, and numerous deblurring networks have been ...
Shayma Wail Nourildean
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Distributed Deblurring of Large Images of Wide Field-Of-View
, 2017 Image deblurring is an economic way to reduce certain degradations (blur and noise) in acquired images. Thus, it has become essential tool in high resolution imaging in many applications, e.g., astronomy, microscopy or computational photography.
Bianchi, Pascal +4 more
core
Single Image Defocus Deblurring Based on Structural Information Enhancement
IEEE AccessDefocus deblurring is an important task in computer vision that aims to bring images back to clarity. Over recent years, both blind defocuse deblurring and non-blind defocuse deblurring methods have made great progress in the single image defocus ...
Guangming Feng +3 more
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Deblured Gaussian Blurred Images
, 2010 Journal of Computing online at https://sites.google.com/site/journalofcomputing/
Al-amri, Salem Saleh +2 more
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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 +4 more
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Turbulent image deblurring using a deblurred blur kernel
Journal of OpticsAbstract In the context of addressing a noisy turbulence-degraded image, it is common to use a denoising low-pass filter before implementing a deblurring algorithm. However, this filter not only suppresses noise but also induces a certain degree of blur into the degraded image.
Lizhen Duan, Libo Zhong, Jianlin Zhang
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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 +4 more
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, 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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A Novel Fractional-Order Non-Convex TVα,p Model in Image Deblurring
Fractal and FractionalIn 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
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Semantic-aware Image Deblurring
, 2019 Image deblurring has achieved exciting progress in recent years. However, traditional methods fail to deblur severely blurred images, where semantic contents appears ambiguously. In this paper, we conduct image deblurring guided by the semantic contents inferred from image captioning.
Chen, Fuhai +8 more
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