Results 271 to 280 of about 2,065,913 (297)

A Novel SVM-Based Blind Super-Resolution Algorithm

The 2006 IEEE International Joint Conference on Neural Network Proceedings, 2006
In this paper, we propose a novel support vector machines (SVM)-based method of blind super-resolution (SR) image restoration. First, a blur identification method is proposed to identify the blur parameter of the acquisition system from the compressed/uncompressed low-resolution image.
Jianping Qiao, Ju Liu, Caihua Zhao
openaire   +1 more source

PSF Recovery from Examples for Blind Super-Resolution

2007 IEEE International Conference on Image Processing, 2007
This paper addresses the problem of super-resolving a single image and recovering the characteristics of the sensor using a learning-based approach. In particular, the point spread function (PSF) of the camera is sought by minimizing the mean Euclidean distance function between patches from the input frame and from degraded versions of high-resolution ...
Isabelle Bégin, Frank P. Ferrie
openaire   +1 more source

Degradation Regression with Uncertainty for Blind Super-Resolution

Neurocomputing, 2023
Shang Li, Guixuan Zhang, Zhengxiong Luo 0001, Jie Liu 0028, Zhi Zeng, Shuwu Zhang   +5 more
openaire   +1 more source

Multi-Image Blind Super-Resolution of 3D Scenes

IEEE Transactions on Image Processing, 2017
We address the problem of estimating the latent high-resolution (HR) image of a 3D scene from a set of non-uniformly motion blurred low-resolution (LR) images captured in the burst mode using a hand-held camera. Existing blind super-resolution (SR) techniques that account for motion blur are restricted to fronto-parallel planar scenes.
Abhijith Punnappurath, Thekke Madam Nimisha, Ambasamudram Narayanan Rajagopalan   +2 more
openaire   +2 more sources

A single image based blind super-resolution approach

2008 15th IEEE International Conference on Image Processing, 2008
In this paper, we address the problem of producing super- resolved image from a single low-resolution input. Unlike most previous work, the camera's point spread function (PSF) is not assumed to be known in advance and the single image super-resolution problem is formulated as a blind deconvolution problem under a MAP framework which can be optimized ...
Wei Zhang 0021, Wai-kuen Cham
openaire   +2 more sources

Blind Super-Resolution with Deep Convolutional Neural Networks

2016
Example-based methods have demonstrated their ability to perform well for Single Image Super-Resolution (SR). While very efficient when a single image formation model (non-blind) is assumed for the low-resolution (LR) observations, they fail when a LR image is not compliant with this model, producing noticeable artifacts on the final SR image.
Clément Peyrard, Moez Baccouche, Christophe Garcia   +2 more
openaire   +1 more source

Kernel Estimation Network for Blind Super-Resolution

ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022
Xiang Cao, Haibo Shen, Liangqi Zhang, Yihao Luo, Tianjiang Wang   +4 more
openaire   +2 more sources

Reference-Based Blind Super-Resolution Kernel Estimation

2022 IEEE International Conference on Image Processing (ICIP), 2022
Mehmet Yamac, Aakif Nawaz, Baran Ataman
openaire   +2 more sources

From general to specific: Online updating for blind super-resolution

Pattern Recognition, 2022
Guixuan Zhang, Shuwu Zhang, Shang Li
exaly  

From degrade to upgrade: Learning a self-supervised degradation guided adaptive network for blind remote sensing image super-resolution

Information Fusion, 2023
Liangpei Zhang, Qiangqiang Yuan, Kui Jiang   +2 more
exaly