Perceptual Multimedia Encoding with Pre-defined Quality Patterns
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Solution Overview
Problem
Conventional Region of Interest (ROI) encoding systems are time-consuming and inefficient due to the lack of pre-defined quality patterns, leading to inconsistent encoding settings that may not align with viewer preferences, and fail to optimize compression ratio and performance while maintaining perceptual quality.
Innovation Solution
The implementation of pre-defined encoding quality patterns that adjust quality settings for different areas of an image or video frame, allowing for higher compression ratios and faster processing by allocating bits based on defined high, mid, and low quality areas, with optional filter application for non-supporting encoders.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional ROI encoding is used without pre-defined patterns, then encoding flexibility is maintained, but encoding time increases and consistency decreases
Solution Approach 1:
The patent applies preliminary action by pre-defining multiple encoding quality patterns (e.g., patterns for different UI layouts, logo positions, and content types) before the actual encoding process. These patterns are stored in a database and automatically selected based on the input content characteristics, eliminating the need for time-consuming manual region definition during encoding.
Solution Approach 2:
The system implements self-service by automatically analyzing input content characteristics (such as detecting UI elements, logos, or content type) and autonomously selecting the most appropriate pre-defined encoding pattern, without requiring manual user intervention for region definition or quality parameter adjustment.
2Manufacturing precision
If manual ROI definition is used, then encoding quality can be customized, but encoding consistency across different users and systems decreases
Solution Approach 1:
The patent applies parameter changes by defining multiple pre-configured encoding quality patterns with different quality parameters (QP values, bit allocation strategies) for different regions and content types. The system automatically adjusts these parameters based on the selected pattern, ensuring consistent encoding quality across different users and systems without requiring manual parameter tuning.
Solution Approach 2:
The system implements universality by creating a library of versatile pre-defined encoding patterns that can handle various content types (videos with UI, images with logos, different aspect ratios) through a unified framework. A single pattern selection mechanism serves multiple encoding scenarios, making the system universally applicable across different use cases.
3Loss of substance
If uniform quality encoding is applied to entire frames, then simplicity is maintained, but compression ratio and bandwidth efficiency decrease
Solution Approach 1:
The patent applies segmentation by dividing the encoding frame into multiple regions with different quality settings based on pre-defined patterns. Different regions (e.g., UI areas, logo positions, main content areas) are assigned different quality parameters and bit allocation strategies, allowing selective compression that improves overall bandwidth efficiency while maintaining quality where needed.
Solution Approach 2:
The system implements copying by reusing pre-defined encoding quality patterns across multiple encoding operations. Once a pattern is created and validated, it can be copied and applied to similar content types, reducing the complexity of pattern management while achieving consistent results across different encoding tasks.
4Measurement precision
If content-dependent ROI analysis is performed, then encoding accuracy improves, but processing time and computational resources increase
Solution Approach 1:
The patent applies preliminary action by pre-analyzing and categorizing different content types and UI layouts during pattern creation. The pre-defined patterns contain pre-computed region definitions and quality parameters for various content scenarios, allowing the encoding system to quickly match input content to the most appropriate pattern without performing complex real-time content analysis.
Solution Approach 2:
The system implements feedback by incorporating content analysis results to automatically select and adjust the appropriate pre-defined encoding pattern. The system analyzes input content characteristics, provides feedback to the pattern selection mechanism, and automatically adjusts the encoding parameters based on this feedback, achieving high accuracy without manual intervention.
Data Source
AI summary
An image and video compression method includes defining one or more encoding quality patterns, the one or more encoding quality patterns each have pre-determined areas of quality adjustment, the pre-determined areas of quality adjustment including one or more pre-defined regions of lower quality adjustment and one or more pre-defined regions of higher quality adjustment; receiving a frame associated with content to be encoded; selecting one of the one or more encoding quality patterns; processing the frame via an encoder, the processing using the selected one of the one or more encoded quality patterns; and producing a final output of an encoded bit.