CFMB-T: A cross-frequency multi-branch transformer for low-quality infrared remote sensing image super-resolution
Authors:
- Yuan CaoYCYuan Cao
- Ligang LiLLLigang Li
- Bo LiuBLBo Liu
- Wenbo ZhouWZWenbo Zhou
- Zengyi LiZLZengyi Li
- Wei NiWNWei Ni
- 12 August 2023
- journal article
- research article
- Published by Elsevier in Infrared Physics & Technology
- Vol. 133
Abstract
No abstract availableKeywords
This publication has 23 references indexed in Scilit:
- Accelerating the Super-Resolution Convolutional Neural Network2016
- Accurate Image Super-Resolution Using Very Deep Convolutional Networks2016
- Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network2016
- Image Super-Resolution Using Deep Convolutional NetworksIEEE Transactions on Pattern Analysis and Machine Intelligence, 2015
- Super-resolution image reconstruction: a technical overviewIEEE Signal Processing Magazine, 2003
- Atmospheric turbulence modulation transfer function for infrared target acquisition modelingOptical Engineering, 2001
- Analytical method to calculate optical transfer functions for image motion and vibrations using momentsJournal of the Optical Society of America A, 1997
- A stability criterion for biorthogonal wavelet bases and their related subband coding schemeDuke Mathematical Journal, 1992
- Backpropagation Applied to Handwritten Zip Code RecognitionNeural Computation, 1989
- High-resolution image recovery from image-plane arrays, using convex projectionsJournal of the Optical Society of America A, 1989