Attention Network with Outdoor Illumination Variation Prior for Spectral Reconstruction from RGB Images | |
Song, Liyao1; Li, Haiwei2; Liu, Song3; Chen, Junyu2; Fan, Jiancun4; Wang, Quan2; Chanussot, Jocelyn5 | |
作者部门 | 光谱成像技术研究室 |
2023-01 | |
发表期刊 | REMOTE SENSING |
ISSN | 2072-4292 |
卷号 | 16期号:1 |
产权排序 | 2 |
摘要 | Hyperspectral images (HSIs) are widely used to identify and characterize objects in scenes of interest, but they are associated with high acquisition costs and low spatial resolutions. With the development of deep learning, HSI reconstruction from low-cost and high-spatial-resolution RGB images has attracted widespread attention. It is an inexpensive way to obtain HSIs via the spectral reconstruction (SR) of RGB data. However, due to a lack of consideration of outdoor solar illumination variation in existing reconstruction methods, the accuracy of outdoor SR remains limited. In this paper, we present an attention neural network based on an adaptive weighted attention network (AWAN), which considers outdoor solar illumination variation by prior illumination information being introduced into the network through a basic 2D block. To verify our network, we conduct experiments on our Variational Illumination Hyperspectral (VIHS) dataset, which is composed of natural HSIs and corresponding RGB and illumination data. The raw HSIs are taken on a portable HS camera, and RGB images are resampled directly from the corresponding HSIs, which are not affected by illumination under CIE-1964 Standard Illuminant. Illumination data are acquired with an outdoor illumination measuring device (IMD). Compared to other methods and the reconstructed results not considering solar illumination variation, our reconstruction results have higher accuracy and perform well in similarity evaluations and classifications using supervised and unsupervised methods. |
关键词 | hyperspectral reconstruction illumination variation attention network |
DOI | 10.3390/rs16010180 |
收录类别 | SCI ; EI |
语种 | 英语 |
WOS记录号 | WOS:001141352200001 |
出版者 | MDPI |
EI入藏号 | 20240315384638 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.opt.ac.cn/handle/181661/97157 |
专题 | 光谱成像技术研究室 |
通讯作者 | Li, Haiwei |
作者单位 | 1.Xian Technol Univ, Inst Artificial Intelligence & Data Sci, Xian 710021, Peoples R China 2.Chinese Acad Sci, Xian Inst Opt & Precis Mech, Xian 710119, Peoples R China 3.Nanchang Hangkong Univ, Sch Measuring & Opt Engn, Nanchang 330063, Peoples R China 4.Xi An Jiao Tong Univ, Sch Informat & Commun Engn, Xian 710049, Peoples R China 5.Univ Grenoble Alpes, Grenoble INP, GIPSA Lab, CNRS, F-38000 Grenoble, France |
推荐引用方式 GB/T 7714 | Song, Liyao,Li, Haiwei,Liu, Song,et al. Attention Network with Outdoor Illumination Variation Prior for Spectral Reconstruction from RGB Images[J]. REMOTE SENSING,2023,16(1). |
APA | Song, Liyao.,Li, Haiwei.,Liu, Song.,Chen, Junyu.,Fan, Jiancun.,...&Chanussot, Jocelyn.(2023).Attention Network with Outdoor Illumination Variation Prior for Spectral Reconstruction from RGB Images.REMOTE SENSING,16(1). |
MLA | Song, Liyao,et al."Attention Network with Outdoor Illumination Variation Prior for Spectral Reconstruction from RGB Images".REMOTE SENSING 16.1(2023). |
条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Attention Network wi(22292KB) | 期刊论文 | 出版稿 | 限制开放 | CC BY-NC-SA | 请求全文 |
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