Stratified Object-Oriented Image Classification Based on Remote Sensing Image Scene Division
The traditional remote sensing image segmentation method uses the same set of parameters for the entire image. However, due to objects’ scale-dependent nature, the optimal segmentation parameters for an overall image may not be suitable for all objects. According to the idea of spatial dependence, t...
Main Authors: | Wen Zhou, Dongping Ming, Lu Xu, Hanqing Bao, Min Wang |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2018-01-01
|
Series: | Journal of Spectroscopy |
Online Access: | http://dx.doi.org/10.1155/2018/3918954 |
Similar Items
-
Hybrid Collaborative Representation for Remote-Sensing Image Scene Classification
by: Bao-Di Liu, et al.
Published: (2018-12-01) -
Semisupervised Center Loss for Remote Sensing Image Scene Classification
by: Jun Zhang, et al.
Published: (2020-01-01) -
Remote Sensing Image Scene Classification with Noisy Label Distillation
by: Rui Zhang, et al.
Published: (2020-07-01) -
CNN-Based Land Cover Classification Combining Stratified Segmentation and Fusion of Point Cloud and Very High-Spatial Resolution Remote Sensing Image Data
by: Keqi Zhou, et al.
Published: (2019-09-01) -
FEATURE FUSION FOR CROSS-MODAL SCENE CLASSIFICATION OF REMOTE SENSING IMAGE
by: W. Geng, et al.
Published: (2021-08-01)