Low Resolution Motion Estimation Pipeline for Video Encoding
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Solution Overview
Problem
Existing video encoding systems face challenges in efficiently encoding image data, particularly for higher resolution images, due to the computational complexity of determining encoding parameters, which can hinder real-time or near real-time transmission and display.
Innovation Solution
The implementation of a low resolution pipeline in parallel with the main encoding pipeline, which determines encoding parameters using low-resolution image data derived from source image data, allowing for reduced memory bandwidth and improved operational efficiency by performing motion estimation searches ahead of the main pipeline.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If full-resolution image data is used for motion estimation searches, then motion estimation accuracy is improved, but computational complexity and processing time increase significantly
Solution Approach 1:
The patent divides the motion estimation process into two segments: a first motion estimation search performed on downsampled/low-resolution image data to identify candidate motion vectors, and a second motion estimation search performed on full-resolution image data using only those candidate vectors. This segmentation reduces the overall computational complexity while maintaining motion estimation accuracy.
Solution Approach 2:
The patent performs a preliminary motion estimation search on downsampled image data before the main motion estimation search on full-resolution data. This preliminary action identifies candidate motion vectors that narrow down the search space for the subsequent full-resolution search, reducing computational complexity while preserving accuracy.
2Measurement precision
If full-resolution image data is used for motion estimation searches, then motion estimation accuracy is improved, but processing time increases
Solution Approach 1:
The patent segments the motion estimation process into two time-efficient stages: a fast preliminary search on downsampled data that quickly identifies candidate vectors, and a focused second search on full-resolution data using only those candidates. This segmentation significantly reduces total processing time compared to performing a single exhaustive search on full-resolution data.
Solution Approach 2:
The patent performs a preliminary motion estimation search on downsampled image data before the main motion estimation search. This preliminary action reduces the search space for the subsequent full-resolution search, thereby reducing processing time while maintaining accuracy.
3Device complexity
If downsampled image data is used for motion estimation searches, then computational complexity is reduced, but motion estimation accuracy deteriorates
Solution Approach 1:
The patent uses downsampled image data for the first motion estimation search to reduce computational complexity, then performs a second motion estimation search on full-resolution image data using the candidate motion vectors identified in the first search. This two-stage segmentation ensures that accuracy is restored in the final step while benefiting from reduced complexity in the preliminary step.
Solution Approach 2:
The patent performs a preliminary motion estimation search on downsampled image data to identify candidate motion vectors, which are then used to guide the second search on full-resolution data. This preliminary action on reduced-complexity data does not compromise final accuracy because the candidate vectors are refined in the second search stage.
4Measurement precision
If multiple motion estimation searches are performed, then motion estimation accuracy is improved, but processing time increases
Solution Approach 1:
The patent divides the multiple motion estimation searches into two distinct segments: a first search on downsampled data with a larger search range to identify candidates, and a second search on full-resolution data with a focused search range using the candidates. This segmentation optimizes the balance between accuracy and processing time by avoiding redundant searches.
Solution Approach 2:
The patent performs a preliminary motion estimation search that identifies candidate motion vectors, which are then used to constrain and guide the second search. This preliminary action reduces the effective search space for the second search, thereby reducing processing time despite performing multiple searches.
Data Source
AI summary
A video encoding system encodes source image data corresponding with an image includes a low resolution pipeline that receives the source image data corresponding with a first coding block in the image. The low resolution pipeline includes a low resolution motion estimation block programmed to generate a first downscaled coding block by downscaling resolution of the source image data corresponding with the first coding block. The first downscaled coding block comprises a first downscaled prediction block corresponding with a first prediction block in the first coding block. The low resolution pipeline may also perform several low resolution motion estimation searches to generate motion vector candidates. The video encoding system also includes a main pipeline that receives the source image data and determines encoding parameters to be used to encode the first coding block based at least partially on the motion vector candidates.