Multiscale Augmented Normalizing Flows for Image Compression

Most learning-based image compression methods lack efficiency for high image quality due to their non-invertible design. The decoding function of the frequently applied compressive autoencoder architecture is only an approximated inverse of the encoding transform. This issue can be resolved by using...

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Veröffentlicht in:	Proceedings of the ... IEEE International Conference on Acoustics, Speech and Signal Processing (1998) S. 3030 - 3034
Hauptverfasser:	Windsheimer, Marc, Brand, Fabian, Kaup, Andre
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 14.04.2024
Schlagworte:	Adaptation models augmented normalizing flows Bit rate end-to-end image compression hierarchical image compression Image coding Image resolution Learning-based image compression Quantization (signal) rate distortion optimization Speech processing Transforms
ISSN:	2379-190X
Online-Zugang:	Volltext
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