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Super-resolution: a comprehensive survey
Super-resolution, the process of obtaining one or more high-resolution images from one or
more low-resolution observations, has been a very attractive research topic over the last two …
more low-resolution observations, has been a very attractive research topic over the last two …
A review on Single Image Super Resolution techniques using generative adversarial network
Abstract Single Image Super Resolution (SISR) is a process to obtain a high pixel density
and refined details from a low resolution (LR) image to get upscaled and sharper high …
and refined details from a low resolution (LR) image to get upscaled and sharper high …
TTST: A Top-k Token Selective Transformer for Remote Sensing Image Super-Resolution
Transformer-based method has demonstrated promising performance in image super-
resolution tasks, due to its long-range and global aggregation capability. However, the …
resolution tasks, due to its long-range and global aggregation capability. However, the …
Details or artifacts: A locally discriminative learning approach to realistic image super-resolution
Single image super-resolution (SISR) with generative adversarial networks (GAN) has
recently attracted increasing attention due to its potentials to generate rich details. However …
recently attracted increasing attention due to its potentials to generate rich details. However …
Structure-preserving super resolution with gradient guidance
Structures matter in single image super resolution (SISR). Recent studies benefiting from
generative adversarial network (GAN) have promoted the development of SISR by …
generative adversarial network (GAN) have promoted the development of SISR by …
Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network
Recently, several models based on deep neural networks have achieved great success in
terms of both reconstruction accuracy and computational performance for single image …
terms of both reconstruction accuracy and computational performance for single image …
Efficient and degradation-adaptive network for real-world image super-resolution
Efficient and effective real-world image super-resolution (Real-ISR) is a challenging task
due to the unknown complex degradation of real-world images and the limited computation …
due to the unknown complex degradation of real-world images and the limited computation …
Single image super-resolution from transformed self-exemplars
Self-similarity based super-resolution (SR) algorithms are able to produce visually pleasing
results without extensive training on external databases. Such algorithms exploit the …
results without extensive training on external databases. Such algorithms exploit the …
Learning a no-reference quality metric for single-image super-resolution
Numerous single-image super-resolution algorithms have been proposed in the literature,
but few studies address the problem of performance evaluation based on visual perception …
but few studies address the problem of performance evaluation based on visual perception …
A novel fuzzy hierarchical fusion attention convolution neural network for medical image super-resolution reconstruction
The clarity of medical images is crucial for doctors to identify and diagnose different
diseases. High-resolution images have more detailed information and clearer content than …
diseases. High-resolution images have more detailed information and clearer content than …