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Remote Targets Recognition Based on Adaptive Weighting Feature Dictionaries and Joint Sparse Representations

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Abstract

With the improvement in resolution, more and more useful information is contained in the space of remote sensing images, which makes the processing of remote sensing data become more complex, and it is easy to cause the curse of dimensionality and the poor recognition effect. In this paper, a remote target recognition approach named AJRC is proposed, which uses joint feature dictionary for sparse representation based on different feature information for adaptive weighting. Firstly, the features of the images are extracted to calculate the contribution weight of each eigenvalue in sparse representation, and each eigenvalue contribution weight is calculated in sparse representation. Through the adaptive method, the contribution ability of each feature value in sparse representation is strengthened, and new atoms are formed to construct feature dictionary, which makes the dictionary more discriminative. Then, the common features of each category image and the private features of a single image are extracted from the feature vector, and a joint dictionary is formed to represent the test image sparse and recognize the output of the target. Aiming at the problem that the target visual contrast difference, the low resolution and the rotation of the target with different angles, the experiment is carried out by different feature extraction methods. At the same time, we use the PCA method to reduce the feature dictionary in order to avoid dimensionality. Experiments show that compared with the existing SRC method and JSM method, this method has better recognition rate.

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Authors and Affiliations

  1. Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation, School of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha, 410114, Hunan, People’s Republic of China

    Wei Wang, Junwu Chen, Ji Li & Xin Wang

Authors
  1. Wei Wang
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  2. Junwu Chen
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  3. Ji Li
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  4. Xin Wang
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Corresponding authors

Correspondence to Ji Li or Xin Wang.

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Wang, W., Chen, J., Li, J. et al. Remote Targets Recognition Based on Adaptive Weighting Feature Dictionaries and Joint Sparse Representations. J Indian Soc Remote Sens 46, 1863–1870 (2018). https://doi.org/10.1007/s12524-018-0836-5

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  • DOI: https://doi.org/10.1007/s12524-018-0836-5

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