Frequency-Assisted Mamba for Remote Sensing Image Super-Resolution

arXiv:2405.04964v1 Announce Type: new
Abstract: Recent progress in remote sensing image (RSI) super-resolution (SR) has exhibited remarkable performance using deep neural networks, e.g., Convolutional Neural Networks and Transformers. However, existing SR methods often suffer from either a limited receptive field or quadratic computational overhead, resulting in sub-optimal global representation and unacceptable computational costs in large-scale RSI. To alleviate these issues, we develop the first attempt to integrate the Vision State Space Model (Mamba) for RSI-SR, which specializes in processing large-scale …

abstract arxiv computational convolutional convolutional neural networks costs cs.cv global however image mamba networks neural networks performance progress representation resolution sensing transformers type