Networked Image Processing Bandwidth Adaptation
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Solution Overview
Problem
Current telecommunications networks face degradation due to high data volume transmissions of image/video data, which can be mitigated by dynamically adjusting data transmission based on network bandwidth, while maintaining display quality without requiring users to have detailed knowledge of network communications.
Innovation Solution
A distributed image/video processing system that estimates available network bandwidth and applies image/video enhancement and compression techniques to reduce data volume, using noise reduction and compression methods that are compatible with the available bandwidth, ensuring efficient transmission and maintaining image/video quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If large amounts of image/video data are transmitted to central network sites, then processing and storage capacities are utilized, but network performance is significantly degraded
Solution Approach 1:
The system dynamically adjusts image processing parameters and data transmission characteristics based on real-time network conditions. The processor varies compression levels, data quality settings, and transmission parameters according to current network bandwidth and performance metrics, enabling the system to adapt between high data volume transmission and network performance maintenance.
Solution Approach 2:
The system changes processing parameters such as compression ratio, data quality, and transmission settings based on network conditions. By modifying these parameters dynamically, the system can reduce data volume when network performance degrades while maintaining acceptable image/video quality and processing capabilities.
2Productivity
If image/video data is processed and compressed to reduce data volume, then network transmission efficiency is improved, but processing time and computational complexity increase
Solution Approach 1:
The system dynamically adjusts processing intensity and compression levels based on real-time network conditions and available processing time. When network transmission is urgent or bandwidth is limited, the system applies higher compression and processing algorithms to maximize transmission efficiency. When time is abundant, it uses lighter processing to minimize computational overhead.
Solution Approach 2:
The system performs preliminary network condition assessment and pre-configures processing parameters before actual data transmission. By estimating network bandwidth and conditions in advance, the system can pre-determine optimal compression and processing settings, reducing the time needed for real-time processing adjustments.
3Speed
If network bandwidth is limited, then data transmission capacity is constrained, but image/video quality cannot be maintained
Solution Approach 1:
The system changes data quality parameters, compression levels, and transmission settings based on available network bandwidth. When bandwidth is limited, it adjusts parameters to maintain acceptable image/video quality at lower data rates. When bandwidth is sufficient, it restores higher quality settings, creating a dynamic balance between transmission speed and quality preservation.
Solution Approach 2:
The system continuously monitors network transmission conditions and image/video quality metrics, using this feedback to dynamically adjust processing and transmission parameters. This closed-loop control ensures that quality degradation is minimized while adapting to changing network bandwidth conditions.
4Adaptability or versatility
If users are provided with detailed network communication knowledge to manage data transmission, then control over network usage is improved, but user complexity and operational difficulty increase
Solution Approach 1:
The system performs self-optimization by automatically monitoring network conditions, adjusting processing parameters, and managing data transmission without requiring user intervention. The processor autonomously adapts compression levels and transmission settings based on real-time network state, eliminating the need for users to understand or manually control network communication details.
Solution Approach 2:
The system introduces an intermediary layer between users and network communication mechanisms. This intermediary automatically handles network condition assessment, parameter adjustment, and quality optimization, shielding users from complex network details while maintaining adaptability to network conditions.
Data Source
AI summary
A distributed image/video processing system is disclosed herein wherein one or more of digital image/video recorders (e.g., a digital cameras, video recorders, or smart phones, etc.) are in network communication with central network site for transmitting image or video data thereto. The recorders process their image/video data dependent upon an estimate of a measurement of network bandwidth that is available for transmitting image or video data to the central network site.