Image Region Segmentation for Light Trail Overexposure Control
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Solution Overview
Problem
Current photographing technologies, such as mobile devices and cameras, struggle to capture high-quality images of moving light trails, like fireworks or waterfalls, due to overexposure issues, especially for users without advanced photography experience.
Innovation Solution
A method and apparatus that divide each frame of an image into light trail, background light source, and non-light-source regions based on preset brightness values, allowing for differential processing to prevent overexposure and enhance image sharpness, enabling users to capture high-quality moving light trail images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If a slow shutter is used to capture moving light trails, then the light trail effect is improved, but overexposure occurs in the background light source region
Solution Approach 1:
The image is divided into multiple regions including light trail region, background light source region, and non-light-source region based on brightness thresholds. Different processing strategies are applied to each region to balance light trail capture with overexposure prevention.
Solution Approach 2:
Different brightness adjustment parameters are applied to different regions of the image. The light trail region receives enhanced brightness while the background light source region has its brightness controlled to prevent overexposure, achieving localized quality optimization.
2Manufacturing precision
If manual adjustment of photographing parameters is required, then photographing quality can be improved, but ease of operation deteriorates
Solution Approach 1:
The system automatically performs region segmentation, brightness analysis, and parameter adjustment without requiring user intervention. The device serves itself by intelligently capturing light trails while preventing overexposure through automated processing.
Solution Approach 2:
The system automatically adjusts photographing parameters such as exposure time, ISO sensitivity, and brightness thresholds based on real-time analysis of the captured image content, eliminating the need for manual parameter tuning by users.
3Manufacturing precision
If a single lens reflex camera is used, then photographing quality is improved, but device complexity and portability worsen
Solution Approach 1:
The invention enables ordinary mobile devices with simple cameras to capture high-quality light trail images through software processing, replacing the need for expensive specialized equipment like single lens reflex cameras.
Solution Approach 2:
Complex mechanical systems (tripods, specialized camera mechanisms) are replaced by intelligent image processing algorithms that automatically achieve light trail capture and overexposure prevention through computational methods.
Data Source
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AI summary
A photographing method is disclosed. The method includes: after obtaining an instruction of entering a slow shutter photographing mode, entering the slow shutter photographing mode; continuously obtaining frames of images of a photographed object; dividing each frame of image of the photographed object into a light trail region, a background light source region, and a no-light source region according to a first preset brightness value; merging the light trail regions of the frames of images, and using the merged light trail region as a light trail region of a target image; using the background light source regions of one or more of the frames of images as a background light source region of the target image, to avoid overexposure of the background light source region of the target image; merging the no-light source regions of one or more of the frames of images, and using the merged no-light source region as a no-light source region of the target image, to enhance brightness of the no-light source region of the target image and avoid overexposure; and storing the target image after obtaining a photographing instruction.