Improvement of the example-regression-based super-resolution land cover mapping algorithm
文献类型：期刊论文
| 作者 | Zhang, Yihang1,2; Du, Yun1; Ling, Feng1; Li, Xiaodong1 |
| 刊名 | Ieee geoscience and remote sensing letters
 |
| 出版日期 | 2015-08-01 |
| 卷号 | 12期号:8页码:1740-1744 |
| 关键词 | Example based Subpixel mapping (spm) Super-resolution mapping (srm) Support vector regression (svr) |
| ISSN号 | 1545-598X |
| DOI | 10.1109/lgrs.2015.2423496 |
| 通讯作者 | Ling, feng(lingf@whigg.ac.cn) |
| 英文摘要 | Super-resolution mapping (srm) is a method for generating a fine-resolution land cover map from coarse-resolution fraction images. example-regression-based srm algorithms can estimate a fine-resolution land cover map with detailed spatial information by learning land cover spatial patterns from available land cover maps. existing example-regression-based srm algorithms are sensitive to fraction errors, and the results often include many linear artifacts and speckles. to overcome these shortcomings, this study proposes an improved example-regression-based srm algorithm. the objective function of the proposed srm algorithm comprises three terms. the first term is used to minimize the difference between the fraction values of the estimated fine-resolution land cover map and the input fraction values. the second term is used to maximize the class membership possibility values of the fine pixels in the result. the final term is used to make the result locally smooth. the proposed srm algorithm is compared with several popular srm algorithms using both synthetic and real fraction images. experimental results indicate that the proposed srm algorithm can produce results with less speckles and linear artifacts, more spatial details, smoother boundaries, and higher accuracies than the srm results used for comparison. |
| WOS关键词 | REMOTELY-SENSED IMAGERY ; NEURAL-NETWORK ; REPRESENTATION ; INFORMATION ; MODEL |
| WOS研究方向 | Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology |
| WOS类目 | Geochemistry & Geophysics ; Engineering, Electrical & Electronic ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:000356542100030 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| URI标识 | http://www.irgrid.ac.cn/handle/1471x/2376457 |
| 专题 | 中国科学院大学 |
| 通讯作者 | Ling, Feng |
| 作者单位 | 1.Chinese Acad Sci, Inst Geodesy & Geophys, Wuhan 430077, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100039, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhang, Yihang,Du, Yun,Ling, Feng,et al. Improvement of the example-regression-based super-resolution land cover mapping algorithm[J]. Ieee geoscience and remote sensing letters,2015,12(8):1740-1744. |
| APA | Zhang, Yihang,Du, Yun,Ling, Feng,&Li, Xiaodong.(2015).Improvement of the example-regression-based super-resolution land cover mapping algorithm.Ieee geoscience and remote sensing letters,12(8),1740-1744. |
| MLA | Zhang, Yihang,et al."Improvement of the example-regression-based super-resolution land cover mapping algorithm".Ieee geoscience and remote sensing letters 12.8(2015):1740-1744. |
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来源：中国科学院大学
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