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Detail Information Prior Net for Remote Sensing Image Pansharpening
| Content Provider | MDPI |
|---|---|
| Author | Xie, Yuchen Wu, Wei Yang, Haiping Wu, Ning Shen, Ying |
| Copyright Year | 2021 |
| Description | Pansharpening, which fuses the panchromatic (PAN) band with multispectral (MS) bands to obtain an MS image with spatial resolution of the PAN images, has been a popular topic in remote sensing applications in recent years. Although the deep-learning-based pansharpening algorithm has achieved better performance than traditional methods, the fusion extracts insufficient spatial information from a PAN image, producing low-quality pansharpened images. To address this problem, this paper proposes a novel progressive PAN-injected fusion method based on superresolution (SR). The network extracts the detail features of a PAN image by using two-stream PAN input; uses a feature fusion unit (FFU) to gradually inject low-frequency PAN features, with high-frequency PAN features added after subpixel convolution; uses a plain autoencoder to inject the extracted PAN features; and applies a structural similarity index measure (SSIM) loss to focus on the structural quality. Experiments performed on different datasets indicate that the proposed method outperforms several state-of-the-art pansharpening methods in both visual appearance and objective indexes, and the SSIM loss can help improve the pansharpened quality on the original dataset. |
| Starting Page | 2800 |
| e-ISSN | 20724292 |
| DOI | 10.3390/rs13142800 |
| Journal | Remote Sensing |
| Issue Number | 14 |
| Volume Number | 13 |
| Language | English |
| Publisher | MDPI |
| Publisher Date | 2021-07-16 |
| Access Restriction | Open |
| Subject Keyword | Remote Sensing Imaging Science Image Fusion Pansharpening Feature Fusion Unit Superresolution |
| Content Type | Text |
| Resource Type | Article |
