Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline

Journals

Article Types

Countries / Regions

Search Results (1)

Search Parameters:
Keywords = RHLBP

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
28 pages, 5272 KB  
Article
Segmentation-Based PolSAR Image Classification Using Visual Features: RHLBP and Color Features
by Jian Cheng, Yaqi Ji and Haijun Liu
Remote Sens. 2015, 7(5), 6079-6106; https://doi.org/10.3390/rs70506079 - 15 May 2015
Cited by 25 | Viewed by 6598
Abstract
A segmentation-based fully-polarimetric synthetic aperture radar (PolSAR) image classification method that incorporates texture features and color features is designed and implemented. This method is based on the framework that conjunctively uses statistical region merging (SRM) for segmentation and support vector machine (SVM) for [...] Read more.
A segmentation-based fully-polarimetric synthetic aperture radar (PolSAR) image classification method that incorporates texture features and color features is designed and implemented. This method is based on the framework that conjunctively uses statistical region merging (SRM) for segmentation and support vector machine (SVM) for classification. In the segmentation step, we propose an improved local binary pattern (LBP) operator named the regional homogeneity local binary pattern (RHLBP) to guarantee the regional homogeneity in PolSAR images. In the classification step, the color features extracted from false color images are applied to improve the classification accuracy. The RHLBP operator and color features can provide discriminative information to separate those pixels and regions with similar polarimetric features, which are from different classes. Extensive experimental comparison results with conventional methods on L-band PolSAR data demonstrate the effectiveness of our proposed method for PolSAR image classification. Full article
Show Figures

Back to TopTop