Ieee Geoscience and Remote Sensing Letters Fusion of Global and Local Descriptors for Remote Sensing Image Classification

By Vladimir Risojevi´c, Zdenka Babi´c

Subfields: Computer Vision and Pattern Recognition, Remote Sensing

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The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Liangpei Zhang
2. Xiaoqiang Lu
3. Gui-Song Xia
4. Qian Du
5. Yanfei Zhong
6. Xuelong Li
7. Xiang Bai
8. Junwei Han

In Remote Sensing

1. Liangpei Zhang
2. Yanfei Zhong
3. Gui-Song Xia
4. Jingwen Hu
5. Fan Hu
6. Xiaoqiang Lu
7. Qian Du
8. Qi Wang

Citations in the corpus

• Land Use Classification in Remote Sensing Images by Convolutional Neural Networks (2015, background): “Another trend is towards the combination of different features, pursued for example in [31], [32], [33].”
• Gabor-Filtering-Based Completed Local Binary Patterns for Land-Use Scene Classification (2015, methodology): “In [9], a global feature descriptor named enhanced Gabor texture descriptor (EGTD) and a local scale-invariant feature transform (SIFT) [10] descriptor were combined in a hierarchical approach to improve the remote sensing image classification performance.”
• Remote Sensing Image Scene Classification Using Multi-Scale Completed Local Binary Patterns and Fisher Vectors (2016, methodology): “In [11], global features extracted using the enhanced Gabor texture descriptor (EGTD) and local features extracted using the SIFT descriptor were fused in a hierarchical approach to improve the performance of remote sensing image scene classification.”
• Scene Classification With Recurrent Attention of VHR Remote Sensing Images (2019, background): “of multiple different features is considered as a promising approach to seek further promotion [28], [31], [32].”
• AID: A Benchmark Data Set for Performance Evaluation of Aerial Scene Classification (2016, methodology): “This data set is widely used for the task of aerial image classification [2]–[4], [7], [8], [10], [13], [15], [16], [18]–[20], [22]–[27], [30], [32]–[39], [58].”
• Land-use scene classification using multi-scale completed local binary patterns (2016, methodology): “An enhanced Gabor texture descriptor (EGTD) [11] was a global image descriptor based on crosscorrelation between spatial frequency subbands of Gabor image decomposition.”
• SAR-SIFT: A SIFT-Like Algorithm for SAR Images (2015, methodology): “Image classification is performed by Risojevic and Babic [8] using SIFT descriptors within a BoW representation.”