Video Encoding Using Depth Value Distribution for Coding Efficiency
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Solution Overview
Problem
Existing video encoding methods fail to efficiently utilize depth information for encoding two-dimensional videos, leading to increased calculation complexity and suboptimal coding efficiency and image quality.
Innovation Solution
The method involves extracting depth value distribution information from a current largest coding unit (LCU), predicting division structure candidates based on this information, and determining the optimum division structure by considering coding efficiency and image quality, while omitting unnecessary rate-distortion cost calculations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional video encoding methods are used without depth information, then encoding simplicity is maintained, but coding efficiency and image quality deteriorate
Solution Approach 1:
The patent applies preliminary action by extracting depth value distribution information from the current Largest Coding Unit (LCU) before performing division structure determination. This pre-extraction of depth information allows the encoder to predict object structures in advance, enabling more efficient coding decisions without substantially increasing overall encoding complexity. The depth value distribution is obtained prior to candidate generation and evaluation stages.
Solution Approach 2:
The patent applies local quality by using depth information specifically for determining division structures at different coding unit levels. Instead of uniformly applying complex encoding throughout, the method selectively utilizes depth value distribution to guide division structure selection where it provides the most benefit, particularly in regions with distinct depth variations corresponding to object boundaries.
2Manufacturing precision
If comprehensive rate-distortion cost calculations are performed for all division structure candidates, then optimal coding efficiency is achieved, but calculation complexity increases
Solution Approach 1:
The patent applies partial action by performing rate-distortion cost calculations selectively rather than comprehensively for all possible division structure candidates. The method generates multiple division structure candidates based on depth value distribution, then evaluates them using rate-distortion cost calculations to determine the optimum structure. This selective evaluation approach reduces calculation complexity while still achieving optimal or near-optimal coding efficiency.
3Productivity
If depth information is extracted and used for predicting division structures, then coding efficiency improves, but encoding complexity increases
Solution Approach 1:
The patent applies preliminary action by extracting depth value distribution information from the current LCU at an early stage before division structure determination. This pre-extraction allows subsequent prediction and evaluation steps to utilize readily available depth information, improving encoding efficiency without requiring repeated depth analysis during the coding process.
Solution Approach 2:
The patent applies partial action by using depth information selectively for generating and evaluating division structure candidates rather than processing all possible structures. The method generates a set of candidates based on depth value distribution characteristics and evaluates only these candidates, reducing processing complexity compared to exhaustive search while maintaining improved encoding efficiency.
Data Source
AI summary
A method of encoding an image using a depth information includes: extracting a depth value distribution information of a current largest coding unit (LCU); predicting a plurality of division structure candidates of the LCU based on the depth value distribution information; and determining an optimum division structure among the plurality of division structure candidates of the LCU based on at least one of coding efficiency and image quality.