Adaptive Pixel Scanning for Video Macroblock Encoding
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Solution Overview
Problem
Existing video encoding techniques, such as those in the H.264 standard, face inefficiencies in predicting macroblocks, especially in natural images with combined textures and contours, as they rely on fixed scanning orders and are not optimized for macroblock-level prediction, leading to increased bit rates and potential error propagation.
Innovation Solution
A method that assigns encoding priority to pixels in a macroblock based on predetermined criteria, adapts the scanning order, and uses template matching to predict pixels, allowing for adaptive prediction and reduced bit rates by optimizing the prediction quality and scanning order within the macroblock.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If fixed scanning order is used for macroblock prediction, then encoding complexity is reduced, but prediction quality deteriorates leading to increased bit rates
Solution Approach 1:
The patent applies dynamics by making the scanning order adaptive rather than fixed. The scanning order is dynamically adjusted based on the characteristics of the current macroblock and previously decoded pixels, allowing the encoding process to adapt to different image regions and content types, thereby improving prediction quality without excessively increasing complexity
Solution Approach 2:
The patent changes the scanning order parameter based on local image characteristics. By modifying the scanning sequence according to the specific macroblock being encoded and the availability of neighboring pixels, the system optimizes prediction accuracy for different regions while maintaining manageable encoding complexity
2Loss of information
If template matching is used for pixel prediction, then prediction quality improves, but encoding complexity increases
Solution Approach 1:
The patent applies local quality by performing template matching selectively rather than uniformly across the entire macroblock. The approach uses different prediction strategies for different regions based on local characteristics, applying template matching where it provides the most benefit while using simpler methods elsewhere, thus improving overall prediction quality while controlling complexity
Solution Approach 2:
The patent segments the macroblock processing into different regions based on the availability of neighboring pixels and local image characteristics. By dividing the macroblock into zones that can be processed with different scanning orders and prediction methods, the system reduces the overall encoding complexity while maintaining high prediction quality in critical regions
3Loss of information
If adaptive scanning order is implemented, then prediction quality improves, but device complexity increases
Solution Approach 1:
The patent implements dynamics by making the scanning order adaptive to local image characteristics and macroblock content. The scanning sequence is dynamically determined based on the specific requirements of each macroblock region, allowing the system to optimize prediction quality for different image structures while managing device complexity through rule-based adaptation
Solution Approach 2:
The patent changes scanning order parameters based on local image characteristics and macroblock properties. By adjusting the scanning sequence parameter according to the specific encoding context, the system improves prediction quality without requiring complex optimization algorithms, thus controlling device complexity
Data Source
AI summary
A method is provided for encoding at least one image, divided into macroblocks, one macroblock including a set of blocks de pixels. The method includes, for at least one current macroblock of a current image, at least two iterations of the following steps: allocation of a priority level for encoding to at least one pixel of the current macroblock, selection of a pixel with the highest priority level called the priority pixel, prediction of a set of pixels including the priority pixel and a step of encoding a remainder from prediction for a region made up of predicted pixels of the macroblock, called the predicted region, the encoding step being used as and when the predicted region meets a predetermined encoding criterion.