Video Frame Noise Detection via Motion Vector Correlation
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Solution Overview
Problem
Existing video compression techniques face challenges in efficiently detecting and managing high-level white noise in video frames, particularly in motion estimation systems that do not account for motion vector difference overhead costs, leading to increased data transmission and processing loads.
Innovation Solution
A method that calculates the correlation of motion vectors between adjacent macroblocks and compares it to a threshold value to detect white noise, adjusting the quantization step size based on the presence of noise, and uses the ratio of intramode to intermode encoded macroblocks as an additional criterion to determine noise levels, thereby adapting the quantization process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If motion compensated DPCM with block-by-block estimation is used, then data transmission volume is reduced, but motion estimation precision deteriorates
Solution Approach 1:
The patent divides the video frame into macroblocks and further into sub-blocks for motion estimation. This segmentation allows the system to process smaller regions independently, reducing the overall data transmission volume while maintaining acceptable motion estimation precision through selective application of estimation techniques on different segments.
Solution Approach 2:
The patent applies different motion estimation strategies to different regions based on their characteristics. Intra-mode encoding is used for regions with significant motion or noise (requiring higher precision), while inter-mode encoding is used for static or smoothly moving regions (allowing data reduction). This local differentiation resolves the contradiction by optimizing precision where needed and reducing data where acceptable.
2Measurement precision
If pixel-by-pixel motion estimation is used, then motion estimation precision is improved, but processing load increases
Solution Approach 1:
The patent segments the frame into macroblocks and sub-blocks, avoiding the need for full pixel-by-pixel estimation across the entire frame. This segmentation reduces processing load by limiting detailed estimation to smaller, localized regions while using coarser estimation for the rest, thus resolving the contradiction between precision and processing load.
Solution Approach 2:
The patent applies full precision motion estimation only partially - specifically for intra-mode encoded macroblocks that require it. For inter-mode blocks, less precise but faster estimation methods are used. This partial application of high-precision estimation reduces overall processing load while maintaining necessary precision where required.
3Quantity of substance
If coarse quantization is applied, then data compression is improved, but image quality deteriorates
Solution Approach 1:
The patent applies different quantization strategies to different macroblocks based on their noise characteristics and motion properties. Intra-mode macroblocks (indicating noise or significant motion) receive finer quantization to preserve quality, while inter-mode macroblocks (static or smoothly moving regions) receive coarser quantization for better compression. This local differentiation resolves the contradiction between compression ratio and image quality.
Solution Approach 2:
The patent uses the encoding mode selection (intra vs. inter) as feedback about the local image characteristics to dynamically adjust quantization strength. This feedback mechanism ensures that quantization is adapted to local conditions, achieving good compression where possible while preserving quality where necessary, thus resolving the contradiction.
Data Source
AI summary
A system and/or method for detecting white noise in a sequence of video frames, and a computer program product is described to affect the quantization step size. In the method/system the correlation between motion vectors of macroblocks is calculated and compared to a predefined threshold. The correlation between motion vectors is used as an indicator for noise in the frames. The quantization step size is then adapted according to the detected level of noise.