Endoscope Video Signal Processing Error Correction
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Solution Overview
Problem
Existing endoscope video signal processing systems fail to accurately determine and correct errors in unique parameter data, leading to potential corruption of image output parameters due to noise, which can result in incorrect image display on monitors.
Innovation Solution
A video signal processing apparatus that includes a data reading section to read parameter data from the endoscope's memory, an error determination section to assess parameter data integrity, and a control section to adjust signal processing based on error types, ensuring accurate image output by controlling the signal processing circuit according to the nature of the error.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If parameter data is read from endoscope memory without error verification, then data reading speed is maintained, but data integrity deteriorates due to noise corruption
Solution Approach 1:
The error determination section performs error checking on parameter data immediately after reading from the endoscope memory, before the data is used for image processing. This preliminary verification prevents corrupted data from affecting image output while maintaining efficient data flow through the system.
Solution Approach 2:
The error determination section acts as an intermediary between the data reading section and the signal processing circuit. It verifies data integrity and passes only valid data to subsequent processing stages, preventing noise-corrupted data from degrading image quality without requiring complex retransmission protocols.
2Measurement precision
If error correction is performed for all parameter data, then data accuracy is improved, but processing time increases
Solution Approach 1:
The control section applies different handling strategies based on the type of parameter data and the nature of errors detected. Critical parameters affecting image output receive thorough error correction, while less critical parameters use simpler verification methods, optimizing the balance between accuracy and processing time.
Solution Approach 2:
The system changes its error handling approach based on the specific parameter being processed. For parameters directly affecting image quality, stringent error checking and correction is applied. For other parameters, the system uses more efficient verification methods, dynamically adjusting processing intensity to minimize time loss.
3Loss of information
If the system displays error messages for all parameter errors, then complete error information is provided, but user confusion increases due to false alarms from noise
Solution Approach 1:
The error determination section pre-evaluates detected errors to distinguish between genuine parameter corruption and noise-induced false errors before presenting information to the user. This preliminary filtering ensures that only meaningful errors are communicated, reducing user confusion while maintaining information completeness.
Solution Approach 2:
The control section uses feedback from the error determination section to intelligently select which errors to communicate to the user. The system provides feedback about the reliability of detected errors and adjusts error messaging accordingly, presenting only credible errors to avoid user confusion while maintaining complete error tracking internally.
Data Source
AI summary
A processor includes: a data transmission/reception section that reads parameter data unique to a scope from a ROM provided in the scope; a register communication state determination section that determines whether or not the parameter data read from the data transmission/reception section has an error; and a mute control/color bar control section that if a result of the determination by the register communication state determination section indicates that the parameter data has an error, controls an image processing section according to a type of the parameter data having the error.