Multi-task convolution neural network-based lifting scheme for image compression

doi:10.1016/j.patrec.2025.05.001

Multi-task convolution neural network-based lifting scheme for image compression

2025-05-20

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Amel Benazza‐Benyahia

G

Gabriel Dauphin

DOI：10.1016/j.patrec.2025.05.001

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Abstract

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• Investigating neural networks for the design of lifting-based image coding systems. • Building a CNN-based lifting architecture to better capture the local structure of the image to be encoded. • Developing a multi-task learning approach exploiting the similarities between prediction stages. • Illustrating the benefits of the proposed approach compared to recent related works through objective and subjective evaluation.

Multi-task convolution neural network-based lifting scheme for image compression

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