Autofocus Control via Blurriness Equalization
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Solution Overview
Problem
Existing autofocus systems in optical imaging devices face challenges in achieving precise focus due to irregular blurriness values between left and right images, which can lead to inconsistent lens control and suboptimal image clarity.
Innovation Solution
A method involving an imaging system with a lens module, image sensor, and image signal processor that generates and filters image information from left and right images to equalize their blurriness values, allowing for precise control of the lens position based on the filtered blurriness data to achieve autofocus.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If phase detection pixels are used for fast autofocus, then autofocus speed is improved, but autofocus precision deteriorates when optical axis is not coincident with image sensor central axis
Solution Approach 1:
The patent changes the parameter of blurriness value from a subjective perception metric to an objective measurable parameter. By calculating actual blurriness values from image data and using these to drive lens position adjustment, the system achieves both fast and precise autofocus even when optical axis misalignment occurs.
Solution Approach 2:
The patent replaces traditional mechanical focus detection methods with an electronic/image-based approach. Instead of relying on mechanical displacement sensors or subjective focus evaluation, the system uses image signal processing to automatically detect blurriness and control lens position, enabling more precise and reliable autofocus.
2Device complexity
If disparity from images with irregular blurriness values is used for autofocus control, then the method is simple, but image focus precision deteriorates
Solution Approach 1:
The patent performs preliminary action by pre-calculating and storing reference blurriness values for different lens positions. During autofocus operation, the system compares current image blurriness against these pre-stored references to determine the optimal lens position, simplifying the control process while maintaining high precision.
Solution Approach 2:
The patent implements feedback by continuously measuring the actual blurriness value of captured images and using this information to adjust lens position. The system compares current blurriness measurements with reference values and automatically adjusts focus until optimal sharpness is achieved, ensuring both simplicity and precision.
Data Source
AI summary
An autofocus method includes receiving a left image having a first blurriness value and a right image having a second blurriness value, filtering the left image so that the first blurriness value becomes the same as the second blurriness value, and generating a control signal for controlling the lens module based on a difference between a third blurriness value of a filtered left image and the second blurriness value.