Image decoding device, image encoding device, and bitstream transmission device

The image encoding method improves coding efficiency by selectively using affine transformations for complex movements, reducing data and processing load through component-based encoding.

JP7863723B2Active Publication Date: 2026-05-22SUN PATENT TRUST
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Patent Information

Authority / Receiving Office
JP · JP
Patent Type
Patents
Current Assignee / Owner
SUN PATENT TRUST
Filing Date
2025-03-26
Publication Date
2026-05-22

AI Technical Summary

Technical Problem

Conventional image encoding methods struggle with improving coding efficiency when dealing with complex movements such as zooming and rotation, as higher-order motion information like affine transformations require excessive computational resources and increased data encoding.

Method used

An image encoding method that selects transformation components from a set including translation, rotation, scaling, and shear, encoding information to indicate these components, and generates predicted images using the selected components, reducing the amount of information and processing load.

Benefits of technology

This approach enhances encoding efficiency by selectively using affine transformations, reducing the amount of motion information and computational complexity while maintaining prediction accuracy.

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Abstract

To improve coding efficiency.SOLUTION: An image decoding device 200 includes a processing circuit and a storage device accessible from the processing circuit, and the processing circuit uses the storage device to decode from bitstream information that is applied to a plurality of blocks included in a sequence and is used to determine the number of parameters to be used in prediction based on an affine transformation, and generates a predicted image for each of the plurality of blocks included in the sequence by performing prediction based on an affine transformation using a number of parameters selected on the basis of the information, and candidates for the number of parameters to be used in prediction include 4.SELECTED DRAWING: Figure 17
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