Video Compression Rate Control With Picture Look-Ahead
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing video compression systems face challenges in efficiently allocating bits to each picture while maintaining good visual quality and satisfying bandwidth constraints, particularly in scenarios with varying delay and bandwidth requirements across different transmission mediums.
Innovation Solution
Implementing novel rate allocation and rate control algorithms that utilize look-ahead information, past and future picture statistics, and complexity estimation to dynamically adjust coding parameters, ensuring accurate bit allocation and quality control across hierarchical structures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If rate control algorithms vary the number of bits allocated to each picture to achieve target bit rate, then bandwidth constraints are satisfied, but visual quality may deteriorate in complex scenes
Solution Approach 1:
The patent applies local quality by differentiating picture complexity into multiple levels (simple, moderate, complex) and allocating bits differently for each type. Simple pictures receive fewer bits while complex pictures receive more bits, allowing the system to maintain high visual quality where needed while conserving bandwidth in less critical areas.
Solution Approach 2:
The patent changes parameters by using multiple complexity metrics (temporal complexity, spatial complexity, luminance complexity) to dynamically adjust bit allocation. The system modifies the quantization parameter and other coding parameters based on the assessed complexity level, enabling adaptive quality control that responds to scene characteristics.
2Measurement precision
If multiple complexity metrics are used to assess picture complexity, then bit allocation accuracy improves, but computational complexity increases
Solution Approach 1:
The patent segments the complexity assessment into three distinct metrics: temporal complexity (motion-related), spatial complexity (detail-related), and luminance complexity (brightness-related). Each metric is calculated independently and then combined to determine overall picture complexity, allowing for precise assessment while organizing the computational workload into manageable segments.
Solution Approach 2:
The patent performs preliminary action by calculating all complexity metrics during a look-ahead phase before actual encoding. This allows the system to assess future picture complexity in advance and make informed bit allocation decisions without adding computational burden during the time-critical encoding process.
3Manufacturing precision
If look-ahead information is used for rate allocation, then bit target achievement improves, but encoding delay increases
Solution Approach 1:
The patent applies partial action by using a limited look-ahead window that examines only a small number of future pictures (typically 1-3 frames) rather than the entire video sequence. This provides sufficient information for accurate bit allocation while minimizing the delay introduced by the look-ahead process.
Solution Approach 2:
The patent performs preliminary complexity assessment on future pictures during the look-ahead phase, storing the results for later use in bit allocation. This preliminary action enables accurate rate control without requiring actual decoding or full processing of future frames, thereby reducing the time penalty.
4Productivity
If hierarchical picture structures are used, then compression efficiency improves, but rate control difficulty increases
Solution Approach 1:
The patent segments the video stream into a hierarchical structure with I-frames (intra-coded), P-frames (predictive-coded), and B-frames (bi-directional coded). Each frame type has different compression characteristics and bit rate requirements. The rate control system adjusts parameters differently for each frame type, allowing efficient compression while managing complexity through structured differentiation.
Solution Approach 2:
The patent applies local quality by allocating different quality levels to different hierarchical levels. I-frames receive higher quality allocation as they serve as reference frames, while P and B frames receive progressively lower allocation. This ensures that critical reference data maintains high quality while less critical frames can be compressed more aggressively.
Data Source
AI summary
Embodiments feature families of rate allocation and rate control methods that utilize advanced processing of past and future frame/field picture statistics and are designed to operate with one or more coding passes. At least two method families include: a family of methods for a rate allocation with picture look-ahead; and a family of methods for average bit rate (ABR) control methods. At least two other methods for each method family are described. For the first family of methods, some methods may involve intra rate control. For the second family of methods, some methods may involve high complexity ABR control and/or low complexity ABR control. These and other embodiments can involve any of the following: spatial coding parameter adaptation, coding prediction, complexity processing, complexity estimation, complexity filtering, bit rate considerations, quality considerations, coding parameter allocation, and/or hierarchical prediction structures, among others.