Video Coding Block Segmentation for Motion Estimation
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Solution Overview
Problem
Current video coding schemes face inefficiencies in coding moving objects, particularly due to redundancy introduced by rectangular block partitioning along object boundaries, which complicates motion estimation and increases computational complexity.
Innovation Solution
The proposed solution involves an encoding apparatus that partitions video coding blocks into segments using an extension region with additional samples from neighboring blocks, allowing for more precise estimation of segment positions and improved coding efficiency, especially for small blocks in moving scenes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If rectangular block partitioning is used for motion estimation, then the coding structure is simple and easy to implement, but redundancy is introduced along object boundaries and coding efficiency decreases
Solution Approach 1:
The patent applies segmentation by dividing video coding blocks into multiple segments based on detected object boundaries. Instead of treating entire rectangular blocks uniformly, the method segments them into regions that align with actual object boundaries, allowing different motion vectors to be applied to different segments. This resolves the contradiction by maintaining the simplicity of block-based processing while improving coding efficiency through boundary-aware segmentation.
Solution Approach 2:
The patent implements local quality by applying different processing characteristics to different regions within video blocks. Specifically, object boundary detection and segmentation is applied locally at regions where boundaries exist, while uniform block processing is maintained in regions without boundaries. This allows the system to optimize coding efficiency locally at boundaries without compromising the overall simplicity of the rectangular block structure.
2Adaptability or versatility
If geometric motion partitioning is used to partition blocks via straight lines, then flexibility in motion partitioning is improved and approximation of actual motion is better, but computational complexity greatly increases
Solution Approach 1:
The patent applies preliminary action by performing object boundary detection and segmentation before the motion estimation process. By pre-identifying object boundaries and creating segmentation masks, the system prepares the partitioning structure in advance, allowing motion vectors to be efficiently applied to predefined segments without requiring complex real-time optimization during encoding. This reduces computational complexity while maintaining the flexibility of adaptive partitioning.
3Measurement precision
If exhaustive search is performed to find optimal GMP of video coding block, then the motion partitioning accuracy is improved, but computational complexity greatly increases
Solution Approach 1:
The patent extracts the object boundary information from the video content using edge detection or gradient-based methods, and separates this structural information from the motion optimization process. By extracting and utilizing pre-computed boundary locations, the system avoids performing exhaustive searches for optimal partitioning lines, thereby maintaining high motion partitioning accuracy while significantly reducing computational complexity.
4Loss of substance
If object boundary is determined at decoder side using available reference pictures, then the data rate is reduced, but the complexity of determining correct object boundary increases
Solution Approach 1:
The patent uses object boundary detection algorithms as an intermediary process that operates on reference pictures at the decoder side. Instead of transmitting boundary information directly, the system employs local quality analysis and edge detection algorithms to automatically determine boundaries from available reference frames. This intermediary approach reduces data rate by avoiding explicit boundary transmission while managing the detection complexity through established image processing techniques.
Data Source
AI summary
Embodiments of the disclosure relate to an encoding apparatus and a decoding apparatus. The encoding apparatus is configured to process a video signal, the video signal comprising a plurality of frames, each frame being dividable into a plurality of video coding blocks, each video coding block comprising a plurality of pixels. The encoding apparatus comprises a partitioner configured to partition a first video coding block of the plurality of video coding blocks of a first frame of the video signal into a first segment and a second segment, wherein the first segment comprises a first set of the plurality of pixels of the first video coding block and the second segment comprises a second set of the plurality of pixels of the first video coding block.