Endoscopy Video Display Auto-Adjustment for Real-Time Image Quality
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Solution Overview
Problem
Existing endoscopy systems require manual laborious adjustments to optimize video signal display on monitors due to varying examination and image recording conditions, which can be inefficient and time-consuming.
Innovation Solution
An image processing unit generates parameters to automatically adjust the display of the video signal on the monitor based on metadata and control data derived from the video data stream, allowing dynamic and optimized display without user intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual adjustment of display parameters is performed, then display optimization is achieved, but operation time and labor effort increase
Solution Approach 1:
The system performs self-optimization by automatically analyzing the video signal characteristics and adjusting display parameters without requiring manual user intervention. The processing unit evaluates brightness ranges, contrast ratios, and color information to autonomously determine optimal display settings, thereby eliminating the time-consuming manual adjustment process while maintaining display quality.
Solution Approach 2:
The system implements a feedback mechanism where the processed video signal characteristics are continuously monitored and fed back to the display parameter adjustment process. The processing unit analyzes the video signal in real-time and automatically modifies display parameters based on the analyzed characteristics, creating a closed-loop system that continuously optimizes display quality without manual intervention.
2Manufacturing precision
If display parameters are manually adjusted, then display quality is optimized, but device operation complexity increases
Solution Approach 1:
The system eliminates the need for user intervention in display parameter adjustment by implementing automated analysis and control. The processing unit independently evaluates video signal characteristics and determines optimal display parameters, transforming the system from one requiring manual operation to one that self-optimizes display quality.
Solution Approach 2:
The processing unit acts as an intermediary between the video signal source and the display device. It analyzes the video signal characteristics and translates them into appropriate display parameters, serving as an automated mediator that bridges the gap between raw video data and optimized display output without requiring manual user involvement.
3Device complexity
If fixed display parameters are used, then device complexity is reduced, but adaptability to varying recording conditions deteriorates
Solution Approach 1:
The system transitions from static fixed display parameters to dynamic adaptive parameters that automatically adjust based on real-time video signal analysis. The processing unit continuously monitors recording conditions such as lighting, contrast, and color characteristics, and dynamically modifies display parameters accordingly, enabling the system to adapt to varying conditions without increasing operational complexity.
Solution Approach 2:
The system automatically changes display parameters based on the analyzed video signal characteristics. The processing unit modifies parameters such as brightness, contrast, and color space dynamically according to the recording conditions, allowing the display to adapt to different scenarios while maintaining simple operation through automated parameter adjustment.
Data Source
AI summary
To summarize, it is proposed for improving the display of a variable video data stream recorded with a video endoscopy system on a monitor that the video endoscopy system automatically transmits at least one parameter and transmits it to the monitor, wherein the display of a currently transmitted section of the video data stream, preferably in real time, can be adjusted using the parameter to enable an adjusted display of that section on the monitor.