Adaptive locality sensitive analysis representation learning via K-SVD algorithm

Kun Jiang; Zheng Liu; Lei Zhu

doi:10.1117/12.2680377

27 June 2023 Adaptive locality sensitive analysis representation learning via K-SVD algorithm

Kun Jiang, Zheng Liu, Lei Zhu

Proceedings Volume 12705, Fourteenth International Conference on Graphics and Image Processing (ICGIP 2022); 1270528 (2023) https://doi.org/10.1117/12.2680377
Event: Fourteenth International Conference on Graphics and Image Processing (ICGIP 2022), 2022, Nanjing, China

Abstract

Recent years, analysis representation learning and its applications for classification have been well explored and applied, due to its flexible representation ability and low classification complexity. With a learned analysis dictionary, test samples can be transformed into a sparse subspace for classification efficiently. However, the underlying locality of sample data has rarely been explored and reliably married with analysis representation learning to enhance the discriminative capability of the classifier. In this paper, we propose a novel adaptive locality-sensitive analysis representation learning model for pattern classification (ALAR). It considers the intrinsic geometric properties by imposing adaptive weighted constrained graph regularization to uncover the geometric structure of the image data. Through the learned analysis dictionary, we transform the image to a new and compact space where the manifold assumption can be further guaranteed. Thus, the local geometrical structure of images can be preserved in sparse representation coefficients. Moreover, the ALAR model is iteratively solved by the synthesis K-SVD and gradient technique. Experimental results on image classification validate the performance superiority of our ALAR model.

Citation Download Citation

Kun Jiang, Zheng Liu, and Lei Zhu "Adaptive locality sensitive analysis representation learning via K-SVD algorithm", Proc. SPIE 12705, Fourteenth International Conference on Graphics and Image Processing (ICGIP 2022), 1270528 (27 June 2023); https://doi.org/10.1117/12.2680377

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KEYWORDS

Associative arrays

Matrices

Education and training

Image classification

Databases

Statistical analysis

Statistical modeling

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