Intra Prediction Reference Lines for High-Resolution Image Compression
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The increasing resolution and quality of high-definition and ultra-high-definition images result in higher data volumes, leading to increased costs for transmission and storage, necessitating improved image compression techniques.
Innovation Solution
An image encoding and decoding method that utilizes intra prediction with adaptive configuration of reference sample lines, including padding and filtering, to enhance compression efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If higher resolution and quality image data is used, then image quality is improved, but data volume increases leading to higher transmission and storage costs
Solution Approach 1:
The image is divided into multiple blocks that are processed independently using intra-prediction. Each block references samples from neighboring blocks, allowing local compression without losing overall image quality. This segmentation enables efficient compression by processing smaller units with shared reference information.
Solution Approach 2:
Reference sample lines are pre-configured and stored before actual prediction processing. By preparing reference samples in advance and determining their availability status beforehand, the encoding process can proceed more efficiently without repeated availability checks during prediction, reducing computational overhead.
2Quantity of substance
If conventional image compression techniques are used, then data volume is reduced, but compression efficiency is insufficient for high-resolution images
Solution Approach 1:
The system dynamically adapts the intra-prediction process by determining the availability status of reference samples and selectively applying padding or filtering based on actual conditions. The number of reference sample lines and filtering strength are adjusted adaptively rather than using fixed conventional methods, optimizing compression for each specific image region.
Solution Approach 2:
The patent changes key parameters including the number of reference sample lines used for prediction, the filtering strength applied to reference samples, and the padding strategy based on reference sample availability. These parameter adjustments enable the system to achieve better compression efficiency compared to conventional fixed-parameter approaches.
3Productivity
If intra-prediction with reference samples is used, then compression efficiency is improved, but complexity of reference sample configuration increases
Solution Approach 1:
The system automatically determines the availability status of reference samples and performs self-configuration of reference sample lines without requiring complex external control. The encoder autonomously decides whether to pad reference samples, apply filtering, and how many reference lines to use based on the actual image data and boundary conditions, simplifying the overall system architecture.
Solution Approach 2:
Instead of maintaining complex permanent reference sample structures, the system uses temporary reference sample lines that are created as needed during encoding and discarded after use. This approach reduces the complexity of reference sample configuration by using simple, transient data structures rather than complex persistent ones.
Data Source
AI summary
An image encoding/decoding method and apparatus for performing intra prediction using a plurality of reference sample lines are provided. An image decoding method may comprise configuring a plurality of reference sample lines, reconstructing an intra prediction mode of a current block, and performing intra prediction for the current block based on the intra prediction mode and the plurality of reference sample lines.