Name
Title | ||
|---|---|---|
A Deep Joint Network for Multispectral Demosaicking Based on Pseudo-Panchromatic Images |
Abstract | ||
|---|---|---|
Single-sensor multispectral cameras generally utilize a multispectral filter array (MSFA) to sample spatial-spectral information for a reduced capturing time. However, in this situation, each pixel in an MSFA image only contains information from a single channel. Thus, demosaicking is necessary to reconstruct a full-resolution multispectral image from the raw MSFA image. In this paper, we propose a novel end-to-end deep learning framework based on pseudo-panchromatic images (PPIs), which consists of two networks, namely the Deep PPI Generation Network (DPG-Net) and Deep Demosaic Network (DDM-Net). Among them, we first pre-train DPG-Net to reconstruct a full-resolution panchromatic image from the raw MSFA image and then jointly train both networks to recover a full-resolution multispectral image, followed by fine-tuning both networks with fewer restrictions. Experimental results reveal that the proposed method outperforms state-of-the-art traditional and deep learning demosaicking methods both qualitatively and quantitatively. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/JSTSP.2022.3172865 | IEEE Journal of Selected Topics in Signal Processing |
Keywords | DocType | Volume |
Demosaicking,end-to-end deep learning,multispectral filter array,pseudo-panchromatic image | Journal | 16 |
Issue | ISSN | Citations |
4 | 1932-4553 | 0 |
PageRank | References | Authors |
0.34 | 8 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shumin Liu | 1 | 0 | 0.34 |
| Yuge Zhang | 2 | 0 | 0.34 |
| Jie Chen | 3 | 91 | 38.15 |
| Keng Pang Lim | 4 | 0 | 0.34 |
| Susanto Rahardja | 5 | 652 | 102.05 |