Adaptive Image Frame Acquisition for Mobile Photography
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Solution Overview
Problem
Existing methods for photographing with mobile terminals fail to consistently meet user requirements for image quality, as they do not adapt effectively to varying scenarios such as movement states, ambient brightness, and photographic modes, leading to inefficient image acquisition and high power consumption.
Innovation Solution
A method and device for mobile terminals that dynamically adjust the number of images acquired based on the photographing scenario, using modules to determine the optimal number of frames and image quality assessment methods (gradient calculation or deep learning networks) to select or fuse images, ensuring high-quality output while minimizing unnecessary calculations and power usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a fixed number of continuous images are acquired and the best one is selected, then the photographing process is simple and fast, but the image quality cannot consistently meet user requirements across varying scenarios
Solution Approach 1:
The patent applies dynamics by making the number of acquired images adaptive rather than fixed. The system dynamically adjusts the quantity of images to acquire based on real-time scenario analysis (movement state, brightness, photographic mode), transforming a static photographing process into a dynamic one that responds to environmental conditions, thereby improving image quality consistency without excessive complexity
Solution Approach 2:
The patent changes the parameter of image acquisition quantity from a fixed value to a variable determined by scenario conditions. By adjusting this parameter based on movement state, ambient brightness, and photographic mode, the system optimizes image quality while maintaining reasonable processing complexity through conditional logic
2Reliability
If multiple images are acquired to improve selection quality, then image quality may be improved, but power consumption and calculation burden increase
Solution Approach 1:
The patent optimizes the parameter of image acquisition quantity by making it adaptive to scenario conditions. In stable scenarios (low movement, sufficient brightness), the system acquires fewer images to reduce power consumption and calculation. In challenging scenarios (high movement, low brightness), it acquires more images to ensure quality, achieving an optimal balance between image quality and energy usage
Solution Approach 2:
The system dynamically adjusts the number of images acquired based on real-time scenario assessment. This dynamic adaptation allows the system to minimize power consumption and calculation burden in favorable conditions while maintaining high image quality standards in difficult shooting scenarios
3Reliability
If the number of acquired images is increased to ensure quality in movement scenarios, then image quality improves, but the photographing efficiency decreases
Solution Approach 1:
The patent adjusts the image acquisition quantity parameter based on movement detection. When movement is detected, the system increases the number of images acquired to capture at least one high-quality image. When no movement is detected, it reduces the acquisition quantity to maintain photographing efficiency. This conditional parameter adjustment resolves the contradiction between quality and efficiency
4Reliability
If scenario-based adaptive image acquisition is implemented, then image quality and energy efficiency improve, but the control system complexity increases
Solution Approach 1:
The patent segments the scenario analysis into distinct, independent modules: movement state detection, brightness detection, and photographic mode identification. Each module handles a specific aspect of scenario analysis, and their results are combined to determine the final image acquisition quantity. This segmentation reduces control system complexity by breaking down the complex decision-making process into manageable, modular components
Solution Approach 2:
The system uses parameter-based control where the image acquisition quantity is determined by combining results from multiple detection modules. This parameter-driven approach provides a systematic and organized control mechanism that manages complexity through structured decision logic rather than ad-hoc control
Data Source
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AI summary
Provided are a photographing method and device, a mobile terminal and a storage medium. The method includes: responsive to detecting a photographing instruction, continuously acquiring a target number of frames of images meeting a preset photographing parameter, the target number being N and determined by a mobile terminal based on a present photographing scenario and N being a positive integer; and determining a target image according to image quality of the N frames of images and outputting the target image. Through the method, the mobile terminal is more intelligent.