Infrared image super-resolution
4 papers with code • 2 benchmarks • 2 datasets
Aims at upsampling the IR image and create the high resolution image with help of a low resolution image.
results-A
Most implemented papers
Infrared Image Super-Resolution via Transfer Learning and PSRGAN
yongsongH/Infrared_Image_SR_PSRGAN
•
•
IEEE Signal Processing Letters 2021
The depthwise residual block (DWRB) is used to represent the features of the IR image in the main path.
Infrared Image Super-Resolution: Systematic Review, and Future Trends
Image Super-Resolution (SR) is essential for a wide range of computer vision and image processing tasks.
Target-oriented Domain Adaptation for Infrared Image Super-Resolution
DASRGAN operates on the synergy of two key components: 1) Texture-Oriented Adaptation (TOA) to refine texture details meticulously, and 2) Noise-Oriented Adaptation (NOA), dedicated to minimizing noise transfer.
LKFormer: Large Kernel Transformer for Infrared Image Super-Resolution
sad192/large-kernel-transformer
•
•
Given the broad application of infrared technology across diverse fields, there is an increasing emphasis on investigating super-resolution techniques for infrared images within the realm of deep learning.
