Super-Resolution Land Cover Mapping Based on Multiscale Spatial Regularization
Super-Resolution Land Cover Mapping Based on Multiscale Spatial Regularization
复制标题
基于多尺度空间正则化的超分辨率土地覆盖制图
DOI：
10.1109/jstars.2015.2399509
复制
发表时间：
2015-02
影响因子：
5.5
通讯作者：
Deyu Li
中科院分区：
文献类型：
--
作者：
Jianlong Hu;Ge Yong;Yuehong Chen;Deyu Li
超分辨率制图（SRM）是一种根据粗糙影像在精细尺度上划分土地覆盖等级的方法。在空间正则化框架的基础上，提出了一种将细尺度空间信息作为平滑项、粗尺度空间信息作为惩罚项相结合的SRM正则化方法。光滑项被认为是一种均匀性约束，惩罚项被用来表征非均匀性约束。具体来说，平滑项依赖于局部细尺度空间一致性，用于平滑边缘和消除散斑点。惩罚项依赖于粗尺度局部空间差异，在保留更多细节（如线性土地覆盖格局的连通性和聚集性）的同时，抑制了精细尺度信息的过度平滑效应。我们使用模拟和合成图像验证了我们的方法，并将结果与四种代表性的SRM算法进行了比较。数值实验表明，该方法可以生成更精确的地图，减少斑块数量的差异，在视觉上保持更光滑的边缘和更多的细节，抑制斑点点，抑制过度平滑。
Super-resolution mapping (SRM) is a method for allocating land cover classes at a fine scale according to coarse fraction images. Based on a spatial regularization framework, this paper proposes a new regularization method for SRM that integrates multiscale spatial information from the fine scale as a smooth term and from the coarse scale as a penalty term. The smooth term is considered a homogeneity constraint, and the penalty term is used to characterize the heterogeneity constraint. Specifically, the smooth term depends on the local fine scale spatial consistency, and is used to smooth edges and eliminate speckle points. The penalty term depends on the coarse scale local spatial differences, and suppresses the over-smoothing effect from the fine scale information while preserving more details (e.g., connectivity and aggregation of linear land cover patterns). We validated our method using simulated and synthetic images, and compared the results to four representative SRM algorithms. Our numerical experiments demonstrated that the proposed method can produce more accurate maps, reduce differences in the number of patches, visually preserve smoother edges and more details, reject speckle points, and suppress over-smoothing.
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影响因子：
3.4
作者：
Xiaodong Li;Yun Du;F. Ling
通讯作者：
Xiaodong Li;Yun Du;F. Ling
影响因子：
4.8
作者：
M. Q. Nguyen;P. Atkinson;H. Lewis
通讯作者：
M. Q. Nguyen;P. Atkinson;H. Lewis
影响因子：
1.3
作者：
Atkinson, PM
通讯作者：
Atkinson, PM
影响因子：
1.3
作者：
Zhangquan Shen;J. Qi;Ke Wang
通讯作者：
Zhangquan Shen;J. Qi;Ke Wang
DOI：
10.1109/36.917895
发表时间：
2001-04
期刊：
IEEE Trans. Geosci. Remote. Sens.
影响因子：
--
作者：
A. Tatem;H. Lewis;P. Atkinson;M. Nixon
通讯作者：
A. Tatem;H. Lewis;P. Atkinson;M. Nixon