Sub-Block Intra-Frame Prediction with Selective Pixel-Line Filtering
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Solution Overview
Problem
Existing image compression technologies face challenges in efficiently encoding and decoding high-resolution and high-quality images, particularly in intra prediction, which affects encoding/decoding efficiency.
Innovation Solution
The method involves deriving an intra prediction mode for a current block, determining a pixel line for intra prediction, performing filtering on a reference pixel, and selectively applying corrections based on coding parameters and flags, including sub-block partitioning and using Most Probable Mode (MPM) candidates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If intra prediction is performed using conventional methods on entire blocks, then the encoding process is simple, but the encoding/decoding efficiency is insufficient for high-resolution images
Solution Approach 1:
The current block is divided into multiple sub-blocks, and intra prediction is performed separately for each sub-block. This segmentation allows the prediction process to adapt to local variations in high-resolution images, improving encoding efficiency by capturing fine-grained details that would be lost in whole-block prediction.
Solution Approach 2:
Different prediction modes and filtering operations are applied to different sub-blocks based on their local characteristics. The pixel line determination and filtering operations are adapted to local regions, enabling the system to maintain high prediction accuracy across diverse image content while optimizing the complexity for each local area.
2Measurement precision
If filtering is applied to all reference pixels, then prediction accuracy improves, but computational complexity and processing time increase
Solution Approach 1:
Filtering operations are selectively applied only to certain reference pixels based on the determined pixel line and sub-block characteristics, rather than uniformly to all reference pixels. This partial application of filtering maintains prediction accuracy where needed while reducing unnecessary computational overhead in regions where filtering provides minimal benefit.
Solution Approach 2:
The filtering operation parameters are dynamically adjusted based on the intra prediction mode, block size, and determined pixel line. By changing filtering parameters adaptively, the system optimizes the balance between prediction accuracy and processing time, applying stronger filtering only when necessary for maintaining precision.
3Productivity
If sub-block partitioning is implemented for intra prediction, then encoding efficiency improves, but the complexity of determining prediction modes and flags increases
Solution Approach 1:
The block partitioning into sub-blocks is systematically organized with clear partitioning rules and flag definitions. By segmenting the prediction process into manageable sub-block units with standardized handling procedures, the complexity is structured and controllable, enabling efficient processing through repetition of standardized operations across multiple sub-blocks.
Solution Approach 2:
The prediction mode derivation and flag determination are performed in a predetermined sequence and hierarchy. By establishing a clear preliminary framework for mode selection and flag setting before processing individual sub-blocks, the system reduces complexity through systematic organization of the decision-making process, avoiding redundant calculations.
4Measurement precision
If correction operations are applied to prediction pixels, then prediction precision improves, but the number of processing operations and time increase
Solution Approach 1:
Correction operations are applied locally to prediction pixels based on their specific position within sub-blocks and the determined pixel line. By targeting correction operations only to pixels where they provide the most benefit rather than uniformly across all pixels, the system maintains high prediction precision while minimizing the total number of correction operations required.
Solution Approach 2:
The correction operation parameters are dynamically adjusted based on the intra prediction mode, block characteristics, and pixel position. By changing correction parameters adaptively, the system optimizes the balance between prediction precision and processing throughput, applying corrections with appropriate intensity only where necessary.
Data Source
AI summary
An intra-frame prediction method and device, according to the present invention, enables deriving an intra-frame prediction mode of a current block, determining a pixel line, among a plurality of pixel lines, for the intra-frame prediction of the current block, and carrying out the intra-frame prediction of the current block on the basis of the intra-frame prediction mode and the pixel line. In addition, a first reference pixel of the determined pixel line may be selectively filtered, and a prediction pixel of the current block may be selectively corrected, and thus the accuracy of the intra-frame prediction may be improved.