FusionMamba: Efficient Image Fusion with State Space Model

arXiv:2404.07932v1 Announce Type: new
Abstract: Image fusion aims to generate a high-resolution multi/hyper-spectral image by combining a high-resolution image with limited spectral information and a low-resolution image with abundant spectral data. Current deep learning (DL)-based methods for image fusion primarily rely on CNNs or Transformers to extract features and merge different types of data. While CNNs are efficient, their receptive fields are limited, restricting their capacity to capture global context. Conversely, Transformers excel at learning global information but are hindered …

abstract arxiv cnns cs.cv current data deep learning eess.iv extract features fusion generate image information low merge resolution space state state space model transformers type types