Digital Camera Focus Bracketing for In-Focus Still Extraction
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Solution Overview
Problem
Existing image pickup devices struggle to allow users to easily acquire a still picture in focus on a desired image region, as they require complex operations and may miss the optimal focus state during imaging.
Innovation Solution
The digital camera employs a focus bracketing function that captures a moving picture while changing the focus position, generates a focus information table, and allows users to select and record a still picture from the moving picture data based on user-designated regions, ensuring the image is in focus.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If focus bracketing function is used to capture multiple images with different focal positions, then the probability of obtaining an in-focus image is improved, but the imaging time and operational complexity increase
Solution Approach 1:
The camera performs preliminary focus detection on specific regions before capturing the main image. By pre-identifying which regions need focus and calculating optimal focal positions, the system avoids unnecessary captures and directly acquires the in-focus image, significantly reducing imaging time while maintaining high reliability
Solution Approach 2:
Instead of applying uniform focus across the entire image, the system divides the image into multiple regions and performs focus detection and capture only on specific regions of interest. This localized approach reduces the number of required captures and processing time while ensuring critical areas are in focus
2Reliability
If focus bracketing captures multiple images continuously, then the chance of obtaining desired focus state is improved, but the operation complexity increases
Solution Approach 1:
The camera system automatically performs focus detection, calculates optimal focal positions, and captures images without requiring manual user intervention for each step. The system self-manages the entire focus bracketing process, reducing operational complexity while maintaining reliable focus selection
Solution Approach 2:
The system continuously monitors focus evaluation values during the bracketing process and uses this feedback to determine when optimal focus has been achieved. This automated feedback mechanism eliminates the need for manual focus assessment and simplifies user operation
3Measurement precision
If focus detection is performed on the entire image, then the accuracy of focus detection is improved, but the processing time and computational load increase
Solution Approach 1:
The image is divided into multiple regions, and focus detection is performed separately on each region rather than on the entire image at once. This segmentation approach maintains focus detection accuracy for each specific area while significantly reducing overall processing time and computational load
Solution Approach 2:
Focus detection resources are concentrated on specific regions of interest rather than uniformly distributed across the entire image. This localized detection approach improves processing efficiency while maintaining high accuracy where it matters most
Data Source
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Figure 3A~3B
AI summary
Image pickup device (100) includes optical system (110), imaging element (140), image processor (160), input unit (210), and controller (180). Optical system (110) includes a focus lens. Imaging element (140) generates an image signal from optical information that is input via optical system (110). Image processor (160) performs a predetermined process on the image signal generated by imaging element (140), and then generates moving picture data including a plurality of frame images. Input unit (210) receives input of a designated region on an image made by a user. Controller (180) causes image processor (160) to generate the moving picture data while moving a focus position of optical system (110), and then extracts a still picture that is in focus on the designated region from among the plurality of frame images included in the moving picture data.