Resolution Adaptive Video Encoding Search Range Constraint
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Solution Overview
Problem
Conventional video encoding methods face challenges in efficiently handling resolution adaptive video encoding with search range constraints, particularly in scenarios where the current frame and reference frame have different resolutions, leading to increased search buffer size requirements.
Innovation Solution
The proposed solution involves applying a search range constraint on the search range of blocks in the current frame, using a control circuit to limit the search range and ensure it fits within a fixed search buffer size, while encoding blocks with pixel information from a reference frame using inter prediction, even when the current frame's resolution differs from the reference frame's resolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If resolution adaptive video encoding is used to allow frame resolution changes, then encoding flexibility and adaptability are improved, but search buffer size requirements increase
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting the search range based on the resolution difference between current and reference frames. When resolution changes occur, the search range is scaled proportionally to match the resolution ratio, allowing the encoding system to adapt to different resolutions while keeping the search buffer size manageable through controlled parameter adjustment rather than unbounded expansion
Solution Approach 2:
The patent implements dynamics by making the search range adaptive and variable rather than fixed. The search range is dynamically calculated based on the resolution relationship between frames, allowing it to expand or contract according to the specific encoding scenario. This dynamic adjustment enables the system to handle resolution changes efficiently without permanently increasing buffer requirements
2Measurement precision
If search range is expanded to cover effective search area in reference frame, then motion estimation accuracy is improved, but memory buffer size increases
Solution Approach 1:
The patent uses parameter changes to scale the search range according to the resolution ratio between current and reference frames. By adjusting the search range parameter proportionally to the resolution difference, the system maintains appropriate search coverage for accurate motion estimation while preventing unnecessary expansion that would increase buffer size requirements
3Device complexity
If search range constraint is applied to limit buffer size, then device complexity is reduced, but motion estimation accuracy may deteriorate
Solution Approach 1:
The patent resolves this contradiction by intelligently adjusting the search range parameter based on resolution information. The constraint is not arbitrary but is calculated according to the resolution ratio, maintaining sufficient search coverage for accurate motion estimation while keeping the buffer size manageable. This parameter-based adaptation prevents both excessive buffer usage and insufficient search coverage
Data Source
AI summary
An encoding method includes applying a search range constraint on a search range of a block in a current frame, and encoding the block in the current frame with pixel information in a reference frame according to inter prediction performed based on the search range of the block in the current frame, wherein a resolution of the current frame is different from a resolution of the reference frame.