Video Encoding Reference Image Selection Based on Motion Threshold
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Solution Overview
Problem
Existing video coding methods, such as HEVC, face challenges in selecting an optimal reference image for motion prediction, as they often prioritize precision over encoded data amount, leading to inefficient encoding when subject motion is significant or when reference images are temporally distant.
Innovation Solution
An encoding apparatus and method that acquire the motion amount of an encoding target image and select a reference image based on a threshold value, prioritizing either a reference image with a larger encoded data amount for low motion or a closer temporal distance for high motion, to balance encoding efficiency and precision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If a reference image with larger encoded data amount is selected, then the quality of the reference image and encoding target image is improved, but the temporal distance may increase leading to larger motion amount and decreased motion prediction precision
Solution Approach 1:
The patent applies dynamics by making the reference image selection criterion dynamic rather than static. The selecting unit changes its selection strategy based on the motion amount detected in the encoding target image: when motion amount is small, it selects reference images with larger encoded data amount for quality; when motion amount is large, it selects reference images with smaller temporal distance for prediction precision. This dynamic adaptation resolves the contradiction between quality and precision.
2Measurement precision
If a reference image with closer temporal distance is selected, then motion prediction precision is improved, but the encoded data amount may be smaller leading to lower image quality
Solution Approach 1:
The patent resolves this contradiction through dynamic selection criteria. The selecting unit adapts its behavior based on detected motion amount: for images with large motion, it prioritizes temporal proximity for precision; for images with small motion, it prioritizes encoded data amount for quality. This dynamic approach allows the system to optimize for the relevant criterion in each context.
3Quantity of substance
If the encoding target image and reference image are temporally distant, then the motion amount increases, but the encoded data amount may be larger improving image quality
Solution Approach 1:
The patent applies dynamics by switching selection criteria based on motion characteristics. When temporal distance causes large motion amount, the system switches from selecting reference images with large encoded data amount to selecting those with small temporal distance, thereby preventing precision degradation while maintaining quality through the appropriate criterion selection.
Data Source
AI summary
There is provided an encoding apparatus comprising. An acquiring unit acquires a motion amount of an encoding target image. A selecting unit selects a reference image from a plurality of reference image candidates. An encoding unit encodes the encoding target image by motion-compensated predictive coding in which the selected reference image is referenced. If the motion amount is less than a threshold value, the selecting unit selects a reference image candidate having a larger encoded data amount with priority. If the motion amount is greater than the threshold value, the selecting unit selects a reference image candidate having a closer temporal distance from the encoding target image with priority.