Blurring Detection Sensor Offset Removal via Feature Integration
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Solution Overview
Problem
Existing signal processing technologies face challenges in accurately removing offsets from the output signals of blurring detection sensors, such as gyro sensors, due to individual differences and environmental factors like temperature, which affects camera shake correction in imaging devices.
Innovation Solution
A signal processing device and method that extracts and integrates feature amounts from the output signal to calculate and subtract offsets, using both direct current components and gradient-based features, with threshold-based validation and storage for precise offset correction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If offset removal processing is performed using conventional methods, then the offset can be removed from the output signal, but the accuracy of offset removal is insufficient due to individual differences and environmental factors
Solution Approach 1:
The system performs preliminary actions by extracting multiple feature amounts (DC component, gradient of integral value, etc.) before offset calculation, and validates their consistency before finalizing the offset value. This preliminary validation ensures that the offset removal is accurate and reliable under various environmental conditions.
Solution Approach 2:
The system uses feedback by comparing multiple feature amounts extracted from the output signal and validating their consistency. The offset calculation is performed only when the feature amounts are consistent, ensuring reliable offset removal. The system continuously monitors and adjusts based on the validated feature amounts.
2Measurement precision
If multiple feature amounts are extracted and validated for offset calculation, then the offset removal accuracy is improved, but the processing complexity increases
Solution Approach 1:
The offset removal process is segmented into distinct steps: extracting DC component, extracting gradient of integral value, validating consistency between them, and calculating offset only when validated. This segmentation makes the complex processing manageable and systematic, improving accuracy without overwhelming complexity.
Solution Approach 2:
The system dynamically adjusts the offset calculation based on the consistency validation of feature amounts. When feature amounts are consistent, offset calculation is performed; when inconsistent, the system waits for validation. This dynamic approach ensures accuracy while managing processing complexity efficiently.
Data Source
AI summary
Provided are a signal processing device, a signal processing method, a signal processing program, an imaging apparatus, and a lens apparatus capable of accurately removing an offset from an output signal of a blurring detection sensor. The signal processing device comprises the blurring detection sensor and a processor. The processor is configured to execute processing of extracting a first feature amount relating to the offset from the output signal of the blurring detection sensor, processing of integrating the output signal, processing of extracting a second feature amount relating to the offset from a value obtained by integrating the output signal, processing of calculating the offset on the basis of the first feature amount and the second feature amount, and processing of subtracting the calculated offset from the output signal.