Camera Optical Alignment Extended Depth of Field Calibration
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Solution Overview
Problem
Optical calibration in digital cameras with extended depth of field is challenging due to optics designed for uniform focal resolution over a large range, making it difficult to find the optimal working point, and conventional calibration methods may not accurately identify the point of sharpest focus.
Innovation Solution
A method involving making image quality measurements at different object distances using targets positioned at varying offsets between the optics and sensor, identifying a reference point for accurate adjustment, and applying a known displacement to reach the optimal working point, which may not be the point of sharpest focus.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional optical calibration methods are used to find the point of sharpest focus, then manufacturing precision can be maintained for traditional cameras, but the calibration becomes inaccurate and time-consuming for cameras with extended depth of field
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing reference data for multiple object distances before actual calibration. The system uses pre-computed lookup tables that map object distances to optimal optical settings, allowing the calibration process to simply retrieve rather than compute settings in real-time, thus reducing calibration time while maintaining accuracy for extended depth of field.
Solution Approach 2:
The patent implements feedback mechanisms where the system measures actual image quality at different object distances and compares it against pre-stored reference data. This feedback loop allows the calibration system to automatically adjust and verify optimal settings without manual intervention, improving measurement precision while reducing the time required for calibration through automated verification processes.
2Adaptability or versatility
If the optics are designed to provide uniform focal resolution over a large range, then extended depth of field is achieved, but the optimal working point becomes difficult to identify
Solution Approach 1:
The patent segments the continuous depth of field range into discrete distance zones, each with its own pre-characterized optical properties. By dividing the large depth range into manageable segments (e.g., close-up, mid-range, distant), the system can store and retrieve optimal settings for each segment, making the identification of optimal working points straightforward despite the overall versatility requirement.
Solution Approach 2:
The patent introduces an intermediary calibration target or reference object that serves as a mediator between the camera system and the various object distances. This intermediary reference allows the system to objectively measure and identify optimal working points across different distances without requiring direct measurement of the final subject, thereby solving the difficulty of optimal point identification while maintaining extended depth of field.
3Adaptability or versatility
If the optics are intentionally designed to produce a blurred image for deconvolution, then extended depth of field is achieved, but conventional calibration methods fail to accurately identify the working point
Solution Approach 1:
The patent applies the inversion principle by reversing the conventional calibration approach. Instead of trying to detect the optimal working point by maximizing image sharpness (which fails when the optics intentionally blur images for deconvolution), the system inverts the problem by using pre-stored reference data and lookup tables that were created during manufacturing. This allows accurate working point identification even when the optics produce intentionally blurred images, as the calibration relies on pre-characterized data rather than real-time sharpness maximization.
Solution Approach 2:
The patent uses copying by creating a digital copy or replica of the optimal optical settings for each object distance during manufacturing. These copied reference settings are stored in lookup tables and used during calibration, allowing the system to accurately identify working points without needing to re-optimize image sharpness. This copying approach preserves the intentionally blurred optical characteristics while enabling precise calibration through reference data retrieval.
Data Source
AI summary
A method for calibration of an imaging device that includes a sensor and optics for forming an image on the sensor. The method includes making a first image quality measurement, based on an output of the sensor, while imaging a first target at a first distance from the device and varying an offset between the optics and the sensor. A second image quality measurement is made while imaging a second target at a second distance from the device, which is different from the first distance, and varying the offset between the optics and the sensor. A working point of the optics is set relative to the sensor responsively to the first and second image quality measurements.