Image Super-resolution Using Registration of Wavelet Multi-scale Components with Affine Transformation

2013 ◽  
Author(s):  
Yasutaka Matsuo ◽  
Ryoki Takada ◽  
Shinya Iwasaki ◽  
Jiro Katto
Keyword(s):  
Affine Transformation ◽  
Super Resolution ◽  
Multi Scale ◽  
Image Super Resolution

scholarly journals Single image super resolution based on multi-scale structure and non-local smoothing

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Wenyi Wang ◽  
Jun Hu ◽  
Xiaohong Liu ◽  
Jiying Zhao ◽  
Jianwen Chen
Keyword(s):  
Super Resolution ◽  
Principal Component ◽  
Feature Mapping ◽  
Multi Scale ◽  
Non Local ◽  
Image Super Resolution ◽  
Gaussian Blur ◽  
Single Image Super Resolution ◽  
Global And Local ◽  
Bicubic Interpolation

AbstractIn this paper, we propose a hybrid super-resolution method by combining global and local dictionary training in the sparse domain. In order to present and differentiate the feature mapping in different scales, a global dictionary set is trained in multiple structure scales, and a non-linear function is used to choose the appropriate dictionary to initially reconstruct the HR image. In addition, we introduce the Gaussian blur to the LR images to eliminate a widely used but inappropriate assumption that the low resolution (LR) images are generated by bicubic interpolation from high-resolution (HR) images. In order to deal with Gaussian blur, a local dictionary is generated and iteratively updated by K-means principal component analysis (K-PCA) and gradient decent (GD) to model the blur effect during the down-sampling. Compared with the state-of-the-art SR algorithms, the experimental results reveal that the proposed method can produce sharper boundaries and suppress undesired artifacts with the present of Gaussian blur. It implies that our method could be more effect in real applications and that the HR-LR mapping relation is more complicated than bicubic interpolation.

Multi-sensor image super-resolution with fuzzy cluster by using multi-scale and multi-view sparse coding for infrared image

2017 ◽  
Vol 76 (23) ◽  
pp. 24871-24902 ◽  
Author(s):  
Xiaomin Yang ◽  
Wei Wu ◽  
Kai Liu ◽  
Weilong Chen ◽  
Ping Zhang ◽  
...  
Keyword(s):  
Sparse Coding ◽  
Infrared Image ◽  
Super Resolution ◽  
Fuzzy Cluster ◽  
Multi Scale ◽  
Image Super Resolution

Mural Image Super Resolution Reconstruction Based on Multi-Scale Residual Attention Network

2020 ◽  
Vol 57 (16) ◽  
pp. 161012
Author(s):  
徐志刚 Xu Zhigang ◽  
闫娟娟 Yan Juanjuan ◽  
朱红蕾 Zhu Honglei
Keyword(s):  
Super Resolution ◽  
Attention Network ◽  
Multi Scale ◽  
Image Super Resolution

Lightweight Image Super-Resolution by Multi-Scale Aggregation

2020 ◽  
pp. 1-11
Author(s):  
Jin Wan ◽  
Hui Yin ◽  
Zhihao Liu ◽  
Aixin Chong ◽  
Yanting Liu
Keyword(s):  
Super Resolution ◽  
Multi Scale ◽  
Image Super Resolution
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