Geometry-Based Candidate Lists for Efficient Video Coding
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Solution Overview
Problem
Existing video coding techniques face inefficiencies in constructing candidate lists for video coding, particularly in advanced video codecs like HEVC, due to suboptimal use of geometry information for determining priority and insertion order in candidate lists, leading to reduced compression efficiency.
Innovation Solution
Introduce a geometry-based priority system for constructing candidate lists, utilizing distances between current blocks and neighboring blocks to determine the priority and insertion order, specifically for merge and AMVP modes, enhancing context modeling in CABAC coding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional fixed-order candidate list construction is used, then implementation is simple, but compression efficiency is reduced
Solution Approach 1:
The patent implements dynamic candidate list construction by adapting the insertion order based on geometric relationships between current and neighboring blocks. Instead of using a fixed predetermined order, the system calculates distances and adjusts the priority of spatial and temporal candidates dynamically, allowing the candidate list structure to adapt to different block configurations and improve compression efficiency.
Solution Approach 2:
The patent applies local quality by treating different spatial positions and block configurations differently in the candidate list construction. Specifically, it considers the geometric characteristics of individual blocks and their neighbors, adjusting the candidate insertion strategy locally based on distance metrics and spatial relationships rather than applying a uniform approach throughout the video sequence.
2Productivity
If geometry-based adaptive priority is used, then compression efficiency is improved, but computational complexity increases
Solution Approach 1:
The patent changes the parameter used for candidate prioritization from a fixed predetermined order to a dynamic parameter based on geometric distance. By calculating the distance between current blocks and neighboring blocks, the system adjusts the priority parameters of candidate insertion, thereby improving video coding performance through adaptive parameter selection rather than static configuration.
3Productivity
If distance-based candidate reordering is implemented, then merge and AMVP mode efficiency is enhanced, but processing time increases
Solution Approach 1:
The patent performs preliminary geometric calculations and distance computations before the actual candidate insertion process. By pre-evaluating the spatial relationships and determining the optimal insertion order in advance, the system reduces the computational burden during the main encoding/decoding process, thereby enhancing merge mode efficiency while minimizing additional processing time.
Data Source
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AI summary
In one example, a device includes a memory configured to store the video data; and one or more processors implemented in circuitry and configured to determine a plurality of distances between a first representative point of a current block of video data and a plurality of second representative points of neighboring blocks to the current block, add one or more of the neighboring blocks as candidates to a candidate list of the current block in an order according to the distances between the first representative point and the second representative points, and code the current block using the candidate list. The candidate list may be, for example, a merge list, an AMVP list, or a most probable mode list. Alternatively, the candidate list may be a list of candidates from which to determine context information for context-adaptive binary arithmetic coding (CABAC).