Polarization image recognition based on cascade deep learning

Jinshan Li; Hantang Chen; Xu Ma; Weili Chen

doi:10.1117/12.2689211

31 July 2023 Polarization image recognition based on cascade deep learning

Jinshan Li, Hantang Chen, Xu Ma, Weili Chen

Proceedings Volume 12747, Third International Conference on Optics and Image Processing (ICOIP 2023); 127471L (2023) https://doi.org/10.1117/12.2689211
Event: Third International Conference on Optics and Image Processing (ICOIP 2023), 2023, Hangzhou, China

Abstract

Polarization imaging technology integrates the spatial and polarization information of the target scene, which can provide high-dimensional light field information to improve the ability of object detection and recognition. The polarization states of natural scenes can be characterized by the Stokes vector ( S₀ , S₁ , S₂ ), degree of polarization ( DoP ) and angle of polarization ( AoP ). In order to better understand and utilize the polarization characteristics, the observers need to recognize the feature maps of different polarization parameters. These images are sometimes hard to distinguish with naked eyes, especially for S₁ and S₂ images due to their similarity. This paper proposes a polarization image recognition method based on the cascade deep learning approach, which can improve the discrimination between S₁ and S₂ images, and achieve preferable recognition accuracy for different kinds of polarization images. We use two ResNet-50 networks successively to classify the polarization images. Firstly, a ResNet-50 network is used to recognize S₀ , S₁₂ , DoP and AoP images, where S₁₂ means the union set of S₁ and S₂ images. Next, the Sobel operation is applied to enhance the discriminat1on of polarization characteristics between S₁ and S₂ images. After that, the second ResNet-50 network is used to separate the images of S₁ and S₂ . It shows that the proposed method outperforms some other comparative methods in terms of recognition accuracy.

Citation Download Citation

Jinshan Li, Hantang Chen, Xu Ma, and Weili Chen "Polarization image recognition based on cascade deep learning", Proc. SPIE 12747, Third International Conference on Optics and Image Processing (ICOIP 2023), 127471L (31 July 2023); https://doi.org/10.1117/12.2689211

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