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1857.11-2024 - IEEE Standard for Neural Network-Based Image Coding | IEEE Standard | IEEE Xplore

1857.11-2024 - IEEE Standard for Neural Network-Based Image Coding

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Status: active - Approved
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Abstract:

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 t...Show More
Scope: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...Show More
Purpose:This standard provides efficient, neural network–based coding tools for compression, decompression, and packaging of image data, which significantly improve the compressi...Show More

Abstract:

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.
Scope:
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.
Purpose:
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). 6 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.
Date of Publication: 20 December 2024
Electronic ISBN:979-8-8557-1415-9
Persistent Link: https://ieeexplore.ieee.org/servlet/opac?punumber=10810314

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