Name
Title | ||
|---|---|---|
SAR Image Classification via Hierarchical Sparse Representation and Multisize Patch Features. |
Abstract | ||
|---|---|---|
In this letter, a novel hierarchical sparse representation-based classification (HSRC) for synthetic aperture radar (SAR) images is proposed. Features utilized in HSRC are extracted from the multisize patches around each pixel to precisely describe the complex terrains. Two thresholds are introduced in the sparse representation classifier to restrict the range of reconstruction residual, which cla... |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/LGRS.2015.2493242 | IEEE Geoscience and Remote Sensing Letters |
Keywords | Field | DocType |
Synthetic aperture radar,Support vector machines,Training,Feature extraction,Remote sensing | Synthetic aperture radar,Remote sensing,Artificial intelligence,Contextual image classification,Computer vision,Pattern recognition,Visualization,Support vector machine,Sparse approximation,Feature extraction,Pixel,Simple Features,Mathematics | Journal |
Volume | Issue | ISSN |
13 | 1 | 1545-598X |
Citations | PageRank | References |
6 | 0.43 | 13 |
Authors | ||
6 | ||