A sampled texture prior for image super-resolution

A sampled texture prior for image super-resolution

Super-resolution aims to produce a high-resolution image from a set of one or more low-resolution images by recovering or inventing plausible high-frequency image content. Typical approaches try to reconstruct a high-resolution image using the sub-pixel displacements of several low- resolution image...

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Bibliografiske detaljer
Main Authors:	Pickup, LC, Roberts, SJ, Zisserman, A
Format:	Conference item
Sprog:	English
Udgivet:	MIT Press 2004

Lignende værker

Bayesian image super-resolution, continued
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Optimizing and learning for super-resolution
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Bayesian methods for image super-resolution
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Super-Resolution Imaging
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Overcoming registration uncertainty in image super-resolution: maximize or marginalize?
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Overcoming Registration Uncertainty in Image Super-Resolution: Maximize or Marginalize?
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Udgivet: (2007-01-01)

Overcoming Registration Uncertainty in Image Super-Resolution: Maximize or Marginalize?
af: Andrew Zisserman, et al.
Udgivet: (2007-01-01)

Machine learning in multi-frame image super-resolution
af: Pickup, L
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Exploiting the image prior in CLIP for super-resolution
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Udgivet: (2024)

Super-resolution enhancement of text image sequences
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Udgivet: (2002)

Exploiting diffusion prior for real-world image super-resolution
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Multi-degradation image super-resolution using texture-transfer
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Double Prior Network for Multidegradation Remote Sensing Image Super-Resolution
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af: Capel, D, et al.
Udgivet: (2003)

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Udgivet: (2023-01-01)

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Discrete Wavelet Transform Sampling for Image Super Resolution
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Reduced-reference quality assessment of image super-resolution by energy change and texture variation
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Udgivet: (2021)

Remote Sensing Image Super-Resolution via Multi-Scale Texture Transfer Network
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Udgivet: (2023-11-01)

Single hyperspectral image super-resolution using a progressive upsampling deep prior network
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A blind image super-resolution network guided by kernel estimation and structural prior knowledge
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Enhancing Cropland Mapping with Spatial Super-Resolution Reconstruction by Optimizing Training Samples for Image Super-Resolution Models
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Forward-Looking Super-Resolution Imaging for Sea-Surface Target with Multi-Prior Bayesian Method
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Udgivet: (2021-12-01)

Radar Forward-looking Super-resolution Imaging Method Based on Sparse and Low-rank Priors
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Udgivet: (2023-04-01)

Assessing resolution in super-resolution imaging
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Udgivet: (2015)

Retinal fundus image super-resolution based on generative adversarial network guided with vascular structure prior
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Unsupervised deep learning method for single image super-resolution of the thick pinhole imaging system using deep image prior
af: Guoguang Li, et al.
Udgivet: (2025-01-01)

TDEGAN: A Texture-Detail-Enhanced Dense Generative Adversarial Network for Remote Sensing Image Super-Resolution
af: Mingqiang Guo, et al.
Udgivet: (2024-06-01)

Image-based rendering using image-based priors
af: Fitzgibbon, A, et al.
Udgivet: (2005)

Image-based rendering using image-based priors
af: Fitzgibbon, A, et al.
Udgivet: (2003)

Component Semantic Prior Guided Generative Adversarial Network for Face Super-Resolution
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