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Implicit Function Super-Resolution Reconstruction Based on Group Propagation Vision Transformer

Jaemin Song
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Retracted: Image Super-Resolution Reconstruction Method for Lung Cancer CT-Scanned Images Based on Neural Network. [PDF]

Biomed Res Int
International BR.
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Improved image quality and diagnostic performance of coronary computed tomography angiography-derived fractional flow reserve with super-resolution deep learning reconstruction

Lan Zou, Xu Cheng, Min Xu, Ke Xu, Ming Wang, Yun Wang, Yining Wang   +6 more
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Biometry and volumetry in multi-centric fetal brain MRI: assessing the bias of super-resolution reconstruction

Sanchez T, Mihailov A, Koob M, Girard N, Manchon A, Valenzuela I, Gómez-Chiari M, Martí Juan G, Pron A, Eixarch E, Piella G, González Ballester MA, Camara O, Dunet V, Auzias G, Bach Cuadra M.   +15 more
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Diffusion-Steered Super-Resolution Image Reconstruction

, 2018
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Super‐resolution image reconstruction using multisensors

Numerical Linear Algebra with Applications, 2004
AbstractSuper‐resolution image reconstruction refers to obtaining an image at a resolution higher than that of a camera (sensor) used in recording the image. In this paper, we present a new joint minimization model in which an objective function is set up consisting of three terms: the data fitting term, the regularization terms for the reconstructed ...
Ng, MK, Yau, AC, Sze, KN, Ching, WK
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Super-resolution image reconstruction

2010 International Conference on Computer Application and System Modeling (ICCASM 2010), 2010
Super-resolution image reconstruction is a technique to reconstruct high resolution image or video from a sequence of low resolution images. The super resolution method is summarized in this paper. The frequency domain method, non-uniform interpolation, POCS method, iterative back projection method, Bayesian approach, regularization method are both ...
null Xue-fen Wan, null Yi Yang
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Super-resolution reconstruction of hyperspectral images

IEEE Transactions on Image Processing, 2005
Hyperspectral images are used for aerial and space imagery applications, including target detection, tracking, agricultural, and natural resource exploration. Unfortunately, atmospheric scattering, secondary illumination, changing viewing angles, and sensor noise degrade the quality of these images.
Toygar, Akgun, Yucel, Altunbasak, Russell M, Mersereau   +2 more
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Context based super resolution image reconstruction

2009 International Workshop on Local and Non-Local Approximation in Image Processing, 2009
In this paper a context based super-resolution (SR) image reconstruction method is proposed. The proposed maximum a-posteriori (MAP) based estimator identifies local gradients and textures for selecting the optimal SR method for the region of interest. Texture segmentation and gradient map estimation are done prior to the reconstruction stage. Gradient
Turgay, Emre, Akar, Gözde
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Stochastic super-resolution image reconstruction

Journal of Visual Communication and Image Representation, 2010
The objective of super-resolution (SR) imaging is to reconstruct a single higher-resolution image based on a set of lower-resolution images that were acquired from the same scene to overcome the limitations of image acquisition process for facilitating better visualization and content recognition.
Jing Tian, Kai-Kuang Ma
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