Imaging Apparatus Automatic Subject Detection Depth Synthesis
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Solution Overview
Problem
Existing imaging technologies struggle to generate images with a deep depth of field, as they often require manual selection of focus points and lack automation in determining the synthesis range, leading to inefficiencies and potential image collapse during focus stacking.
Innovation Solution
An imaging apparatus and method that automatically detect a main subject, determine a synthesis range based on the subject's position, and synthesize image data focused within that range to produce a still image with a deeper depth of field, using a digital camera with an imaging unit, image processor, and controller to handle image data and perform depth synthesis processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual selection of focus points is used, then the operator can select desired subjects, but the process requires user intervention and is inefficient
Solution Approach 1:
The system automatically detects main subjects and determines synthesis ranges without user intervention. The image processor analyzes captured images to identify main subjects based on area and position criteria, then autonomously determines the synthesis range for focus stacking, eliminating the need for manual focus point selection and significantly improving processing efficiency
Solution Approach 2:
The system performs preliminary detection of main subjects and determination of synthesis ranges before executing the focus stacking synthesis. By pre-identifying which subjects to focus on and what range to synthesize, the system prepares the processing parameters in advance, making the subsequent synthesis operation more efficient and automated
2Extent of automation
If automatic main subject detection is implemented, then the process is automated, but the system must accurately identify the most important subject among multiple subjects
Solution Approach 1:
The system applies different evaluation criteria to identify the main subject based on local image characteristics. It calculates the area of each detected subject and determines importance based on whether the subject occupies the center position or a larger area in the image. This localized quality assessment enables accurate automatic identification of the most important subject among multiple subjects
Solution Approach 2:
The system uses parameter changes in subject area and position to determine main subject importance. By analyzing variations in subject area size and center position coordinates, the system dynamically identifies which subject should be the main focus, enabling accurate automation without requiring manual intervention
3Device complexity
If the synthesis range is not properly determined, then processing is simplified, but the synthesis image may collapse or lose quality
Solution Approach 1:
The system performs preliminary determination of the synthesis range based on the detected main subject's position and area before executing the focus stacking synthesis. By pre-calculating the appropriate synthesis range that encompasses the main subject, the system ensures that the synthesis process targets the correct area, preventing image collapse while maintaining processing efficiency
Solution Approach 2:
The system uses feedback from the main subject detection results to dynamically determine the synthesis range. The synthesis range is adjusted based on the detected main subject's characteristics, ensuring that the synthesis process adapts to the actual image content. This feedback mechanism maintains synthesis image quality while keeping the processing methodology consistent
Data Source
AI summary
Imaging apparatus includes imaging unit that captures a subject image while changing an in-focus position to generate a plurality of pieces of image data, image processor that synthesizes the plurality of pieces of image data generated by the imaging unit to generate still image data having a deeper depth of field than a depth of field of each of the plurality of pieces of image data, and controller that controls the image processor. Controller causes image processor to detect a main subject from an image indicated by one image data in the plurality of pieces of image data, determine a range for synthesizing the plurality of pieces of image data based on a position of the detected main subject, and synthesize pieces of image data focused within the determined range to generate the still image data.