9 May 2024 Flotation froth image deblurring algorithm based on disentangled representations
Xianwu Huang, Yuxiao Wang, Zhao Cao, Haili Shang, Jinshan Zhang, Dahua Yu
Author Affiliations +
Abstract

The deblurring of flotation froth images significantly aids in the characterization of coal flotation and fault diagnosis. Images of froth acquired at a flotation site contain considerable noise and blurring, making feature extraction and segmentation processing difficult. We present an effective method for deblurring froth images based on disentangled representations. Disentangled representation is achieved by separating the content and blur features in the blurred image using a content encoder and a blur encoder. Then, the separated feature vectors are embedded into a deblurring framework to deblur the froth image. The experimental results show that this method achieves a superior deblurring effect on froth images under various conditions, which lays the foundation for the intelligent adjustment of parameters to guide the flotation site.

© 2024 SPIE and IS&T
Xianwu Huang, Yuxiao Wang, Zhao Cao, Haili Shang, Jinshan Zhang, and Dahua Yu "Flotation froth image deblurring algorithm based on disentangled representations," Journal of Electronic Imaging 33(3), 033011 (9 May 2024). https://doi.org/10.1117/1.JEI.33.3.033011
Received: 7 November 2023; Accepted: 22 April 2024; Published: 9 May 2024
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KEYWORDS
Deblurring

Feature extraction

Image quality

Image processing

Education and training

Image restoration

Gallium nitride

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