DSC Quantization Parameter Calculation Based on Block Complexity
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Solution Overview
Problem
Conventional video compression techniques, such as display stream compression (DSC), face inefficiencies and artifacts due to inadequate quantization parameter (QP) adjustment values, particularly during transitions from flat to complex image regions and when buffer fullness approaches threshold limits, leading to suboptimal coding efficiency and noticeable artifacts.
Innovation Solution
The method involves determining a complexity value of previous blocks, selecting an appropriate technique for calculating a QP adjustment value based on this complexity, and updating the QP value accordingly to address coding inefficiencies and artifacts, using techniques that adjust QP values more aggressively or conservatively depending on the complexity of image regions and buffer conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional QP adjustment techniques are used, then coding efficiency is maintained at baseline levels, but artifacts appear during transitions from flat to complex image regions and when buffer fullness approaches threshold limits
Solution Approach 1:
The QP adjustment technique dynamically adapts the QP value based on real-time conditions including image complexity (flat vs. complex regions) and buffer fullness thresholds. The system transitions between different QP adjustment strategies depending on these varying conditions, resolving the contradiction by making the compression aggressive in safe conditions and conservative when artifacts are likely to appear.
Solution Approach 2:
The invention changes the QP parameter based on detected image complexity and buffer state. When transitioning from flat to complex regions or when buffer fullness approaches thresholds, the system modifies the QP adjustment value to prevent artifacts, thereby improving picture quality by adapting the compression parameter to current conditions.
2Productivity
If more aggressive QP adjustment is applied to improve coding efficiency, then bandwidth requirements are reduced, but artifacts increase during transitions and buffer threshold conditions
Solution Approach 1:
The system dynamically adjusts the aggressiveness of QP modification based on detected conditions. During flat regions and normal buffer conditions, more aggressive QP adjustment is applied to maximize coding efficiency. During transitions to complex regions or when buffer fullness approaches thresholds, the system reduces aggression to prevent artifacts, thus resolving the contradiction between efficiency and quality.
Solution Approach 2:
The invention modifies the QP parameter adaptively based on image complexity and buffer state. By changing the QP adjustment value according to these conditions, the system achieves high coding efficiency in safe conditions while preventing artifacts during critical transitions, effectively resolving the contradiction between productivity and harmful factors.
3Ease of manufacture
If uniform QP adjustment is applied across all blocks, then implementation is simple, but rate-distortion performance is suboptimal during transitions and buffer threshold conditions
Solution Approach 1:
The invention applies different QP adjustment strategies to different blocks based on their local characteristics (image complexity and buffer state). Rather than uniform adjustment, the system evaluates each block's specific conditions and applies appropriate QP values, improving rate-distortion performance while maintaining reasonable implementation complexity through localized decision-making.
Solution Approach 2:
The system changes the QP parameter based on local block characteristics and global buffer state. This conditional parameter modification improves rate-distortion performance during transitions and buffer threshold conditions while keeping the implementation relatively simple by using straightforward complexity metrics and threshold comparisons.
Data Source
AI summary
Techniques for quantization parameter (QP) for display stream compression (DSC) based on complexity measure are disclosed. In one aspect, a method for determining a QP value includes determining a complexity value of a plurality of previous blocks and selecting a technique from a plurality of defined techniques for calculating a QP adjustment value for a current block based on the determined complexity value. The method may further include calculating the QP adjustment value for the current block via the selected technique and determining the QP value for the current block based on the QP adjustment value.