Image encoding / decoding apparatus and image data transmitting apparatus

By employing a transform-based image coding method that utilizes inverse reduction quadratic transform and inverse first transform, image coding and decoding devices are optimized, solving the problem of efficient compression of high-resolution images/videos, improving coding efficiency and residual coding efficiency, and reducing data transmission and storage costs.

CN117097892BActive Publication Date: 2026-07-10BEIJING XIAOMI MOBILE SOFTWARE CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
BEIJING XIAOMI MOBILE SOFTWARE CO LTD
Filing Date
2019-07-08
Publication Date
2026-07-10

AI Technical Summary

Technical Problem

Existing technologies suffer from high costs due to increased information volume when transmitting and storing high-resolution, high-quality images/videos, and lack effective compression and encoding methods, especially inefficient in immersive media and high frame rate image/video broadcasting.

Method used

A transform-based image coding method is adopted, which optimizes the structure of the image coding and decoding devices through inverse reduced quadratic transform (RST) and inverse first transform, including an entropy decoder, predictor, dequantizer and inverse transform. The mapping relationship between the transform kernel matrix and the intra-frame prediction mode is utilized to improve coding efficiency.

Benefits of technology

By using efficient transformation and quadratic transformation in the frequency domain, non-zero transform coefficients are concentrated in low-frequency components, reducing the amount of residual processing data and improving the overall image/video compression efficiency and residual coding efficiency.

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Abstract

The present application relates to an image encoding / decoding apparatus and an image data transmitting apparatus. An image decoding method according to the present application includes the steps of deriving transform coefficients for a target block by dequantization, deriving modified transform coefficients based on inverse reduced secondary transform (RST) for the transform coefficients, deriving residual samples for the target block based on inverse primary transform for the modified transform coefficients, and generating reconstructed samples based on the residual samples and prediction samples derived based on an intra prediction mode for the target block. The inverse RST is performed based on a transform set. The transform set is determined based on a mapping relationship according to the intra prediction mode applied to the target block. A plurality of intra prediction modes including the intra prediction mode of the target block are mapped to one transform set.
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