Light-field Autofocus System for Camera Focus Accuracy
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Solution Overview
Problem
Conventional autofocus systems in cameras often require iterative and time-consuming methods to determine the optimal focus, which can be inefficient, especially when capturing quick-moving subjects, and may lead to increased battery consumption and mechanical wear.
Innovation Solution
Implementing a light-field based autofocus system that captures a light-field image, generates refocused images at different scene depths, calculates focus metrics, and automatically adjusts the focus motor position to achieve optimal focus without iterative back-and-forth movements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If iterative focus motor stepping and focus metric calculation is used to determine optimal focus, then focus accuracy is improved, but autofocus time increases
Solution Approach 1:
The system performs preliminary actions by capturing a light-field image that contains depth information before the actual focusing process. This preliminary capture of optical flow and depth data allows the system to pre-determine the optimal focus position without requiring time-consuming iterative motor stepping during the focusing operation itself.
Solution Approach 2:
The patent replaces the mechanical iterative stepping process with an optical/computational approach. Instead of physically moving the focus motor through multiple positions and measuring focus metrics mechanically, the system uses light-field imaging to capture depth information optically and computationally determines the optimal focus position through image processing algorithms.
2Measurement precision
If iterative focus motor stepping is used to search for maximum focus metric, then focus precision is improved, but battery life decreases
Solution Approach 1:
The system performs the energy-intensive light-field image capture and depth analysis as a preliminary action before the focusing operation. By completing these computationally heavy tasks in advance using the light-field data, the system avoids repeated iterative focus metric calculations during the actual focusing process, thereby reducing overall energy consumption.
Solution Approach 2:
The patent substitutes the mechanically repetitive focus motor stepping with a single light-field capture operation followed by computational analysis. This replacement eliminates the need for repeated mechanical movements and associated energy consumption, achieving focus precision through optical and computational methods rather than mechanical iteration.
3Measurement precision
If iterative focus motor stepping is used to determine optimal focus, then focus accuracy is improved, but mechanical wear increases
Solution Approach 1:
The system determines the optimal focus position as a preliminary action by analyzing light-field image data captured before the focusing operation. This pre-determination of focus position through optical flow and depth analysis eliminates the need for repeated mechanical stepping during the focusing process, thereby reducing mechanical wear on the focus motor and related components.
Solution Approach 2:
The patent replaces the mechanical iterative focusing process with an optical and computational system. By using light-field imaging to capture depth information and computational algorithms to determine optimal focus position, the system eliminates repeated mechanical movements of the focus motor, thereby reducing mechanical wear and extending component lifespan.
Data Source
AI summary
In various embodiments, the present invention relates to methods, systems, architectures, algorithms, designs, and user interfaces for light-field based autofocus. In response to receiving a focusing request at a camera, a light-field autofocus system captures a light-field image. An image crop that contains a region of interest and a specified border is determined. A series of refocused images are generated for the image crop at different scene depths. A focus metric is calculated for each refocused image. The scene depth of the refocused image with the best focus metric is identified as the appropriate focus. The focus motor position for the appropriate focus is selected and the focus motor is automatically driven to the selected focus motor position.