Mobile Camera Moon Scene Detection and Parameter Adjustment
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Solution Overview
Problem
Mobile terminal cameras struggle to capture high-quality images of the moon due to the long distance and luminance differences between the moon and the night sky, as the Auto mode is not adequately adjusted for these conditions, resulting in poor image quality.
Innovation Solution
An image capturing method that identifies the moon scene using a machine learning model, activating a moon image capturing mode with specific parameters such as local light-measuring for exposure, infinite focal length for focus, and increased zoom range to ensure better image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If Auto mode is used for image capturing, then the system is simple and easy to operate, but the image quality is poor for moon scenes
Solution Approach 1:
The system dynamically switches between Auto mode and Moon mode based on scene recognition. The camera control unit automatically activates Moon mode when a moon scene is detected, adjusting parameters such as exposure time, gain, and focus without requiring manual user intervention. This maintains ease of operation while improving image quality for specific scenarios.
Solution Approach 2:
The system changes multiple imaging parameters simultaneously when Moon mode is activated, including increasing exposure time, adjusting gain values, modifying focus distance, and changing zoom levels. These parameter changes are automatically applied based on scene recognition, resolving the contradiction between simple operation and high image quality.
2Manufacturing precision
If Moon mode is activated with specific parameters, then the image quality is improved, but the device complexity increases
Solution Approach 1:
The system employs self-service through automatic scene recognition and parameter adjustment. The image recognition unit automatically detects moon scenes, and the camera control unit automatically configures appropriate parameters without user intervention. This automation reduces the perceived complexity for users while maintaining high image quality through specialized Moon mode settings.
Solution Approach 2:
The system uses feedback from the image recognition unit to automatically trigger Moon mode when appropriate conditions are detected. This closed-loop control ensures that the complex Moon mode parameters are only activated when needed, balancing image quality improvement with device complexity management through intelligent, condition-based operation.
3Ease of manufacture
If Auto mode parameters are used, then the system is simple to implement, but the exposure and focus are inaccurate for moon scenes
Solution Approach 1:
The system prepares Moon mode parameters in advance for various moon scene conditions. Pre-configured parameter sets including exposure times, gain values, and focus distances are ready to be activated immediately when a moon scene is detected. This preliminary preparation ensures accurate exposure and focus without requiring complex real-time calculations, maintaining ease of manufacture while improving measurement precision.
Data Source
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AI summary
An image capturing method includes: displaying an image capturing preview interface of an image capturing program, the image capturing preview interface displaying a preview image; identifying an image capturing scene of the preview image by calling a machine learning model; and activating a moon image capturing mode in the image capturing program when the image capturing scene is a moon image capturing scene, the moon image capturing mode being an image capturing mode configured to capture image of the moon in a night sky.