scholarly journals An Iterative Super-Resolution Reconstruction of Image Sequences using a Bayesian Approach with BTV prior and Affine Block-Based Registration

2006 ◽  
Author(s):  
V. Patanavijit ◽  
S. Jitapunkul
Keyword(s):  
Bayesian Approach ◽  
Super Resolution ◽  
Image Sequences ◽  
Block Based

scholarly journals Bayesian analysis of data from segmented super-resolution images for quantifying protein clustering

2020 ◽  
Vol 22 (3) ◽  
pp. 1107-1114
Author(s):  
Tina Košuta ◽  
Marta Cullell-Dalmau ◽  
Francesca Cella Zanacchi ◽  
Carlo Manzo
Keyword(s):  
Bayesian Analysis ◽  
Relative Abundance ◽  
Bayesian Approach ◽  
Super Resolution ◽  
Molecular Aggregates ◽  
Protein Clustering ◽  
Precise Quantification

A Bayesian approach enables the precise quantification of the relative abundance of molecular aggregates of different stoichiometry from segmented super-resolution images.

A Video Super Resolution Algorithm Based on Wavelet Coefficient

2014 ◽  
Vol 610 ◽  
pp. 425-428
Author(s):  
Wei Jian Liu ◽  
Si Da Xiao ◽  
Ruo He Yao
Keyword(s):  
High Frequency ◽  
Wavelet Coefficient ◽  
Three Dimensional ◽  
Super Resolution ◽  
Structural Similarity ◽  
Image Sequences ◽  
Discrete Wavelet ◽  
Resolution Image ◽  
Resolution Algorithm ◽  
Visual Results

In this paper, we propose a new super-resolution algorithm based on wavelet coefficient. The proposed algorithm uses discrete wavelet transform (DWT) to decompose the input low-resolution image sequences into four subband images, including LL, LH, HL, HH. Then the input images have been processed by the 3DSKR (Three Dimensional Steering Kernel Regression) super resolution (SR) algorithm, and the result replaces the LL subband image, while the three high-frequency subband images have been interpolated. Finally, combining all these images to generate a new high-resolution image by using inverse DWT. Proposed method has been verified on Calendar and Foliage by Matlab software platform. The peak signal-to-noise (PSNR), structural similarity (SSIM) and visual results are compared, and show that the computational complexity of the proposed algorithm decline by 30 percent compared with the existing algorithm to obtain the approximate results.

scholarly journals Online multi-frame super-resolution of image sequences

2018 ◽  
Vol 2018 (1) ◽  
Author(s):  
Jieping Xu ◽  
Yonghui Liang ◽  
Jin Liu ◽  
Zongfu Huang ◽  
Xuewen Liu
Keyword(s):  
Super Resolution ◽  
Image Sequences

Super-resolution in cardiac MRI using a Bayesian approach

2013 ◽  
Author(s):  
Nelson Velasco Toledo ◽  
Andrea Rueda ◽  
Cristina Santa Marta ◽  
Eduardo Romero
Keyword(s):  
Bayesian Approach ◽  
Cardiac Mri ◽  
Super Resolution

CT super-resolution using multiple dense residual block based GAN

2020 ◽  
Author(s):  
Xiong Zhang ◽  
Congli Feng ◽  
Anhong Wang ◽  
Linlin Yang ◽  
Yawen Hao
Keyword(s):  
Super Resolution ◽  
Block Based ◽  
Residual Block
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