IEEE 1857.11-2024

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IEEE Standard for Neural Network-Based Image Coding

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IEEE 1857.11-2024

IEEE Standard for Neural Network-Based Image Coding

PUBLISH DATE 2024
PAGES 159
IEEE 1857.11-2024

New IEEE Standard - Active.

A set of tools is defined in this standard for efficient image coding, including tools for encoding, for decoding, and for encapsulation.

Some of the tools are based on trained neural networks.

These tools are designed to perform:

  • block partitioning,
  • prediction,
  • transform,
  • quantization,
  • entropy coding,
  • filtering, and so on.

This standard defines a set of tools for *efficient image coding*, including tools for encoding, for decoding, and for encapsulation.

Some of the tools are based on **trained neural networks** and shall perform block partitioning, prediction, transform, quantization, entropy coding, filtering, and so on.

This standard provides efficient, neural network–based coding tools for compression, decompression, and packaging of image data, which significantly improve the compression efficiency compared with IEEE Std 1857.4™-2018 (intrapicture coding) and IEEE Std 1857.10™-2021 (intrapicture coding) under comparable settings, and facilitate the compression and decompression on top of neural network–oriented computing infrastructures like neural network processing units (NPUs).

The target applications and services include but are not limited to Internet images, user-generated images, and other image-enabled applications and services such as digital image storage and communications.

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