General solution to reduce the point spread function effect in subpixel mapping
文献类型:期刊论文
作者 | Wang, Qunming1; Zhang, Chengyuan1; Tong, Xiaohua1; Atkinson, Peter M.2,3,4 |
刊名 | REMOTE SENSING OF ENVIRONMENT
![]() |
出版日期 | 2020-12-15 |
卷号 | 251页码:19 |
关键词 | Remote sensing images Subpixel mapping (SPM) Supper-resolution mapping Downscaling Spectral unmixing Point spread function (PSF) Accuracy assessment |
ISSN号 | 0034-4257 |
DOI | 10.1016/j.rse.2020.112054 |
通讯作者 | Wang, Qunming(wqm11111@126.com) ; Tong, Xiaohua(xhtong@tongji.edu.cn) |
英文摘要 | The point spread function (PSF) effect is ubiquitous in remote sensing images and imposes a fundamental uncertainty on subpixel mapping (SPM). The crucial PSF effect has been neglected in existing SPM methods. This paper proposes a general model to reduce the PSF effect in SPM. The model is applicable to any SPM methods treating spectral unmixing as pre-processing. To demonstrate the advantages of the new technique it was necessary to develop a new approach for accuracy assessment of SPM. To-date, accuracy assessment for SPM has been limited to subpixel classification accuracy, ignoring the performance of reproducing spatial structure in downscaling. In this paper, a new accuracy index is proposed which considers SPM performances in classification and restoration of spatial structure simultaneously. Experimental results show that by considering the PSF effect, more accurate SPM results were produced and small-sized patches and elongated features were restored more satisfactorily. Moreover, using the novel accuracy index, the quantitative evaluation was found to be more consistent with visual evaluation. This paper, thus, addresses directly two of the longest standing challenges in SPM (i.e., the limitations of the PSF effect and accuracy assessment undertaken only on a subpixel-by-subpixel basis). |
WOS关键词 | HOPFIELD NEURAL-NETWORK ; REMOTELY-SENSED IMAGES ; SPATIAL-RESOLUTION ; PIXEL ; ACCURACY ; SEMIVARIOGRAM ; INFORMATION ; ALGORITHMS ; MODEL ; SCALE |
资助项目 | National Natural Science Foundation of China[41971297] ; Fundamental Research Funds for the Central Universities[02502150021] ; Tongji University[02502350047] |
WOS研究方向 | Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology |
语种 | 英语 |
WOS记录号 | WOS:000592407900001 |
出版者 | ELSEVIER SCIENCE INC |
资助机构 | National Natural Science Foundation of China ; Fundamental Research Funds for the Central Universities ; Tongji University |
源URL | [http://ir.igsnrr.ac.cn/handle/311030/156383] ![]() |
专题 | 中国科学院地理科学与资源研究所 |
通讯作者 | Wang, Qunming; Tong, Xiaohua |
作者单位 | 1.Tongji Univ, Coll Surveying & Geoinformat, 1239 Siping Rd, Shanghai 200092, Peoples R China 2.Univ Lancaster, Fac Sci & Technol, Lancaster LA1 4YR, England 3.Univ Southampton, Geog & Environm, Southampton SO17 1BJ, Hants, England 4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Datun Rd, Beijing 100101, Peoples R China |
推荐引用方式 GB/T 7714 | Wang, Qunming,Zhang, Chengyuan,Tong, Xiaohua,et al. General solution to reduce the point spread function effect in subpixel mapping[J]. REMOTE SENSING OF ENVIRONMENT,2020,251:19. |
APA | Wang, Qunming,Zhang, Chengyuan,Tong, Xiaohua,&Atkinson, Peter M..(2020).General solution to reduce the point spread function effect in subpixel mapping.REMOTE SENSING OF ENVIRONMENT,251,19. |
MLA | Wang, Qunming,et al."General solution to reduce the point spread function effect in subpixel mapping".REMOTE SENSING OF ENVIRONMENT 251(2020):19. |
入库方式: OAI收割
来源:地理科学与资源研究所
浏览0
下载0
收藏0
其他版本
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。