Filtered Intra Block Copy Using Gradients for Better Prediction
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Solution Overview
Problem
Existing video coding technologies face challenges in efficiently utilizing spatial and temporal redundancies for improved compression, particularly in intra prediction methods, leading to suboptimal compression efficiency and quality.
Innovation Solution
The implementation of a filtered intra block copy (FIBC) mode that uses a linear filter to predict a current block, combined with gradient and nonlinear values, to enhance prediction accuracy and efficiency by applying a format rule that includes a linear predicted value, gradient value, and location value, utilizing predefined filters and coefficients for improved sample processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional intra prediction methods are used, then device complexity is reduced, but compression efficiency and prediction accuracy deteriorate
Solution Approach 1:
The patent applies parameter changes by introducing gradient values and location values as additional parameters to enhance prediction accuracy. The linear filter uses these parameters to generate more accurate predictions by adapting to local variations in the image data, thereby improving measurement precision without requiring a complete redesign of the prediction system.
Solution Approach 2:
The patent segments the prediction process into multiple stages: generating initial prediction samples, calculating gradient values, determining location values, and applying linear filtering. This segmentation allows each component to be optimized independently while maintaining overall system manageability and reducing complexity.
2Productivity
If filtered intra block copy mode with multiple filters is applied, then compression efficiency is improved, but computational complexity increases
Solution Approach 1:
The patent performs preliminary actions by pre-calculating gradient values and location values before the actual prediction process. These pre-computed parameters are stored and reused during prediction, reducing redundant computations and improving compression efficiency while managing computational complexity through advance preparation.
Solution Approach 2:
The patent introduces intermediary elements (gradient values and location values) that mediate between the raw image data and the final prediction. These intermediaries facilitate more accurate predictions by capturing local characteristics, thereby improving compression efficiency without directly increasing the complexity of the core prediction algorithm.
3Measurement precision
If linear filter with bias term is used, then prediction accuracy is enhanced, but processing overhead increases
Solution Approach 1:
The patent applies local quality by using location values that capture local characteristics of different regions in the image. The linear filter with bias term adapts to local variations by incorporating these location-specific parameters, thereby enhancing prediction accuracy for each local region while maintaining efficient processing through localized rather than global computations.
Data Source
AI summary
Aspects of the disclosure includes methods and apparatuses for video decoding and video encoding and a method of processing visual media data. The apparatus for video decoding includes processing circuitry configured to: receive coded information indicating that a current block in a current picture is predicted using a filtered intra block copy (FIBC) mode; determine a linear predicted value of a current sample in the current block by applying a linear filter to prediction samples predicted using one of an IBC mode and an intra template matching (IntraTMP) mode; determine a gradient value associated with the current sample using at least one gradient filter; determine a predicted value of the current sample based on a sum of the linear predicted value and at least one modification value that includes the gradient value. An FIBC filter in the FIBC mode includes the linear filter and the at least one gradient filter.