Decoding device, encoding device and transmitting device for data of an image
By using the cross-component linear model (CCLM) prediction mode, the problem of high transmission and storage costs for high-resolution images is solved, the efficiency of image coding and intra-frame prediction is improved, and the complexity of image compression is reduced.
CN116916016BActive Publication Date: 2026-06-05LG ELECTRONICS INC
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- LG ELECTRONICS INC
- Filing Date
- 2019-11-11
- Publication Date
- 2026-06-05
AI Technical Summary
Technical Problem
The transmission and storage of high-resolution, high-quality images are costly, and existing technologies struggle to effectively compress image data.
Method used
The cross-component linear model (CCLM) prediction mode is adopted, and the CCLM parameters are calculated by deriving adjacent samples and brightness samples to improve the intra-frame prediction efficiency.
Benefits of technology
It improves image coding efficiency and intra-frame prediction efficiency, and reduces image compression complexity.
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Smart Images
Figure CN116916016B_ABST
Abstract
Decoding device, encoding device, and transmitting device for data of an image. A method for decoding an image performed by a decoding device according to the present document comprises the steps of: deriving, on the basis of prediction mode information, one of a plurality of cross-component linear model (CCLM) prediction modes as a CCLM prediction mode for a luma block; deriving, on the basis of the CCLM prediction mode for the luma block, a size of the luma block, and a specific value, a number of neighboring chroma samples for the luma block; deriving the neighboring chroma samples for the number of neighboring chroma samples; computing CCLM parameters on the basis of the neighboring chroma samples and down-sampled neighboring luma samples; and deriving, on the basis of the CCLM parameters and the down-sampled neighboring luma samples, predicted samples for the luma block, wherein the specific value is derived to be 2.
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