Film Grain Model Parameter Segmentation for Video Coding
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Solution Overview
Problem
Current video coding technologies face inefficiencies in managing film grain models, particularly in bitstream efficiency and parameter sharing across layers, leading to increased bit costs and complexity in encoding and decoding processes.
Innovation Solution
The method involves decoding film grain model syntax elements from a parameter set in the coded data representation, enabling the generation and application of film grain to pictures without reference frames and allowing sharing of film grain model parameters between different layers, thereby reducing bit-savings and simplifying the encoding and decoding processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If separate film grain models are used for each layer, then film grain accuracy is improved, but bit cost and device complexity increase
Solution Approach 1:
The film grain model parameters are segmented into two parts: common parameters shared across all layers and layer-specific parameters. This segmentation allows the system to maintain accurate film grain representation for each layer while avoiding the complexity of managing completely separate models for every layer.
Solution Approach 2:
A single film grain model structure is designed to serve multiple layers simultaneously. The common parameters in the film grain model are universally applied across all layers, while only the necessary layer-specific parameters are maintained separately, reducing overall complexity while preserving accuracy.
2Measurement precision
If film grain parameters are transmitted for each picture, then film grain quality is improved, but bit cost increases
Solution Approach 1:
Film grain model parameters are established and transmitted in advance at the layer level rather than for each individual picture. This preliminary action allows the decoder to have the necessary film grain parameters ready before processing pictures, maintaining quality while significantly reducing the amount of data that needs to be transmitted.
Solution Approach 2:
Instead of transmitting redundant film grain parameters for each picture, the system discards the redundant information and recovers the necessary parameters from the layer-level common parameters and selective picture-level updates, reducing bit cost while maintaining film grain quality.
3Measurement precision
If multiple film grain models are maintained for different layers, then film grain accuracy is improved, but loss of information increases
Solution Approach 1:
Film grain parameters that are common across multiple layers are merged into a single parameter set at the layer level. This merging prevents information loss by ensuring that common parameters are transmitted once and shared efficiently across all layers, rather than being redundantly transmitted or potentially lost in separate model management.
Data Source
AI summary
A decoder can obtain a film grain model syntax element from a parameter set in a coded data representation. The decoder can determine a film grain model value by decoding the film grain model syntax element. The decoder can decode a current picture from the coded data representation. The decoder can generate an output picture by applying generated film grain to the current picture. The decoder can output the output picture.