Dynamic Tag Architecture for Video Processing Adaptability
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Solution Overview
Problem
Existing image processing systems have inefficiencies due to fixed, pre-determined processing algorithms that do not adapt to changing pixel characteristics, leading to redundant functionality, increased manufacturing costs, and reduced image quality.
Innovation Solution
An image processing system that dynamically controls pixel processing operations using meta data or 'tag data' associated with each pixel, allowing for real-time adjustment of processing algorithms based on characteristics such as motion, edge detection, and spatial frequencies, enabling flexible resource allocation and improved image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If fixed, pre-determined processing algorithms are used in prior image processing systems, then device complexity is reduced and ease of manufacture is improved, but adaptability to changing pixel characteristics deteriorates and image quality is reduced
Solution Approach 1:
The patent implements dynamic processing algorithms that automatically adjust processing parameters based on real-time analysis of pixel characteristics such as motion, edge detection, and spatial frequencies. This allows the system to adapt processing operations dynamically without requiring multiple fixed processing paths, resolving the contradiction between ease of manufacture and processing adaptability.
Solution Approach 2:
The system changes processing parameters dynamically based on pixel characteristics. By analyzing features like motion vectors, edge orientations, and spatial frequency content, the system adjusts processing intensity, filter types, and algorithm selection in real-time, enabling adaptability while maintaining a unified processing architecture that remains manufacturable.
2Reliability
If substantially independent processing operations are employed in prior systems, then processing operations can be performed with fixed algorithms, but device complexity increases and manufacturing expense increases
Solution Approach 1:
The patent merges multiple independent processing operations into a unified processing pipeline where a single processing block performs multiple operations sequentially. The system combines motion compensation, deinterlacing, scaling, and other operations in one integrated architecture, reducing silicon implementation size while maintaining reliable processing through systematic operation sequencing.
Solution Approach 2:
The processing block is designed with multi-functionality, capable of performing various image processing operations using a single unified architecture. The system can execute different processing algorithms and operations within the same hardware block, eliminating the need for separate dedicated circuits for each operation and thereby reducing overall device complexity.
3Device complexity
If fixed processing algorithms are used that do not adapt to pixel characteristics, then device complexity is reduced, but image quality deteriorates due to redundant processing
Solution Approach 1:
The patent applies local quality processing by analyzing pixel characteristics such as motion, edges, and spatial frequencies to determine appropriate processing intensity and type for different regions. The system applies adaptive processing parameters locally based on detected features, improving image quality by avoiding redundant processing in uniform regions while enhancing detail in complex regions, all within a unified processing architecture.
Data Source
AI summary
An image processing system and method, in which an image processing operation is performed on a pixel or pixels by selecting and applying one of a plurality of implementations of the image processing operation. The plurality of implementations is varied from time to time, such that one or more of the implementations is replaced with a different implementation or implementations.