Affiliation:
1. School of Information Science and Engineering, Yunnan University, Kunming 650500, China
2. College of Big Data, Yunnan Agricultural University, Kunming 650201, China
Abstract
The objective of pan-sharpening is to effectively fuse high-resolution panchromatic (PAN) images with limited spectral information and low-resolution multispectral (LR-MS) images, thereby generating a fused image with a high spatial resolution and rich spectral information. However, current fusion techniques face significant challenges, including insufficient edge detail, spectral distortion, increased noise, and limited robustness. To address these challenges, we propose a multi-frequency spectral–spatial interaction enhancement network (MFSINet) that comprises the spectral–spatial interactive fusion (SSIF) and multi-frequency feature enhancement (MFFE) subnetworks. The SSIF enhances both spatial and spectral fusion features by optimizing the characteristics of each spectral band through band-aware processing. The MFFE employs a variant of wavelet transform to perform multiresolution analyses on remote sensing scenes, enhancing the spatial resolution, spectral fidelity, and the texture and structural features of the fused images by optimizing directional and spatial properties. Moreover, qualitative analysis and quantitative comparative experiments using the IKONOS and WorldView-2 datasets indicate that this method significantly improves the fidelity and accuracy of the fused images.
Funder
Major Special Science and Technology Project of Yunnan Province