PathSRGAN: Multi-Supervised Super-Resolution for Cytopathological Images Using Generative Adversarial Network.
Jiabo MaJingya YuSibo LiuLi ChenXu LiJie FengZhixing ChenShaoqun ZengXiuli LiuShenghua ChengPublished in: IEEE Trans. Medical Imaging (2020)
Keyphrases
- super resolution
- low resolution images
- high resolution images
- low resolution
- image resolution
- higher resolution
- high resolution
- imaging process
- super resolved
- resolution enhancement
- highest resolution
- image reconstruction
- input image
- image super resolution
- super resolution reconstruction
- image restoration
- degraded images
- test images
- image database
- image quality
- image features
- combining information from multiple
- multiresolution
- single frame
- low quality images
- depth map
- motion estimation
- image data
- spatial resolution
- multi frame
- high quality
- super resolution algorithm
- three dimensional
- unsupervised learning
- generative model
- high resolution video
- image classification
- feature points
- remote sensing
- image patches
- light field
- field of view
- back projection
- edge detection
- single image super resolution
- principal component analysis
- semi supervised
- facial images
- pixel values