Video Coding Alpha Layer Cross-Layer Prediction
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Solution Overview
Problem
Current video coding methods are inefficient for processing alpha channels due to ineffective tools and processes, leading to slow encoding and decoding speeds.
Innovation Solution
The proposed solution involves leveraging cross-layer correlations between base layers and alpha layers, selectively applying coding tools, and interleaving information from different channels to improve prediction accuracy and speed, specifically by disabling ineffective tools and using information from one layer to code another.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If current video coding methods are used for processing alpha channels, then encoding and decoding can be performed, but the processing efficiency is low and encoding/decoding speeds are slow
Solution Approach 1:
The video coding process is segmented into separate base layer and alpha layer processing streams. Each layer is encoded and decoded independently using layer-specific coding tools and parameters, allowing parallel processing and optimized speed for each layer type without compromising overall quality.
Solution Approach 2:
The coding process dynamically adapts by selectively applying different coding tools to different layers based on their specific characteristics. The system can switch between various coding modes and tools depending on the layer type and content requirements, optimizing processing efficiency for each scenario.
2Productivity
If ineffective coding tools are applied to alpha channels, then coding can be performed, but coding efficiency is reduced
Solution Approach 1:
Different coding tools and parameters are applied locally to specific layers based on their unique characteristics. The base layer and alpha layer each receive customized coding treatments tailored to their specific requirements, rather than applying a universal coding approach to all layers.
Solution Approach 2:
The system changes coding parameters and tool selection based on the specific layer being processed. By adapting parameters such as transformation types, prediction modes, and quantization settings to match layer characteristics, coding efficiency is significantly improved while avoiding the use of ineffective tools.
Data Source
AI summary
Example implementations include a method, apparatus and computer-readable medium of video coding, comprising performing a conversion between a video comprising a plurality of pictures and a bitstream of the video, wherein each picture comprises an alpha layer and at least one base layer, and wherein the bitstream comprises first layer information which is utilized in a first process performed on the at least one base layer and second layer information which is utilized in a second process performed on the alpha layer.