BLOCK-BASED COMPRESSIVE AUTO-ENCODER

In one implementation, a picture is partitioned into multiple blocks, with uniform or different block sizes. Each block is compressed by an auto-encoder, which may comprise a deep neural network and entropy encoder. The compressed block may be reconstructed or decoded with another deep neural networ...

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Bibliographic Details
Main Authors BEGAINT, Jean, RACAPE, Fabien, GALPIN, Franck, DUMAS, Thierry
Format Patent
LanguageEnglish
French
German
Published 26.10.2022
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC COMMUNICATION TECHNIQUE
ELECTRICITY
PHYSICS
PICTORIAL COMMUNICATION, e.g. TELEVISION
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Summary:In one implementation, a picture is partitioned into multiple blocks, with uniform or different block sizes. Each block is compressed by an auto-encoder, which may comprise a deep neural network and entropy encoder. The compressed block may be reconstructed or decoded with another deep neural network. Quantization may be used in the encoder side, and de-quantization at the decoder side. When the block is encoded, neighboring blocks may be used as causal information. Latent information can also be used as input to a layer at the encoder or decoder. Vertical and horizontal position information can further be used to encode and decode the image block. A secondary network can be applied to the position information before it is used as input to a layer of the neural network at the encoder or decoder. To reduce blocking artifact, the block may be extended before being input to the encoder.
Bibliography:Application Number: EP20200838321