Cargando…
Kernel Estimation Using Total Variation Guided GAN for Image Super-Resolution
Various super-resolution (SR) kernels in the degradation model deteriorate the performance of the SR algorithms, showing unpleasant artifacts in the output images. Hence, SR kernel estimation has been studied to improve the SR performance in several ways for more than a decade. In particular, a conv...
Autores principales: | Park, Jongeun, Kim, Hansol, Kang, Moon Gi |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10098688/ https://www.ncbi.nlm.nih.gov/pubmed/37050793 http://dx.doi.org/10.3390/s23073734 |
Ejemplares similares
-
Med-SRNet: GAN-Based Medical Image Super-Resolution via High-Resolution Representation Learning
por: Zhang, Lina, et al.
Publicado: (2022) -
Blur Kernel Estimation and Non-Blind Super-Resolution for Power Equipment Infrared Images by Compressed Sensing and Adaptive Regularization
por: Zhao, Hongshan, et al.
Publicado: (2021) -
Accelerating cross-validation with total variation and its application to super-resolution imaging
por: Obuchi, Tomoyuki, et al.
Publicado: (2017) -
FA-GAN: Fused attentive generative adversarial networks for MRI image super-resolution
por: Jiang, Mingfeng, et al.
Publicado: (2021) -
Gram-GAN: Image Super-Resolution Based on Gram Matrix and Discriminator Perceptual Loss
por: Song, Jie, et al.
Publicado: (2023)