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Deep semantic segmentation-based multiple description coding
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DOI：10.1007/s11042-020-09283-w.png)
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Abstract
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In this paper, we propose a deep semantic segmentation-based multiple description coding (DSSMDC). In the proposed scheme, the input image is divided into two different subsets and getting two descriptions, which is named multiple description pre-processing (MDP). Then, two descriptions are encoded and decoded respectively by utilizing the deep semantic segmentation codec, in which the semantic segmentation label is as side information for improving image reconstruction quality. We can get one side reconstruction, when only one description is received at the decoder. If both descriptions are received at the decoder, we can get the central reconstruction. Experimental results show that the proposed scheme achieves better performance than other existing compression methods.
Keywords:
Multiple description coding
Deep semantic segmentation
Generative adversarial network
Compact network
Reconstruction network
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