Continuous Photography Memory-Adaptive Multi-Frame Processing
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Solution Overview
Problem
Existing electronic devices face memory overflow issues during continuous photographing due to long processing durations of multi-frame algorithms, leading to unresponsive photographing and poor user experience.
Innovation Solution
Adaptive selection of processing algorithms and frame quantities based on memory occupation levels to reduce memory pressure and enhance processing efficiency, enabling continuous and fast photographing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If multiple images are captured and merged to improve low-light quality, then the photographing speed decreases and motion blur increases, but the image quality in low-light conditions improves
Solution Approach 1:
The patent applies preliminary action by pre-calculating and determining the merging parameters before actually merging the multiple images. The processor determines the merging parameter based on the plurality of images captured in the low-light scene, which allows for optimized merging that reduces motion blur while maintaining improved image quality. This preliminary determination step enables faster processing of the merging operation itself.
Solution Approach 2:
The patent employs dynamics by adaptively adjusting the merging parameter based on the specific characteristics of the captured images. The merging parameter is not fixed but is dynamically determined based on the plurality of images, allowing the system to optimize the merging process for each specific low-light scenario, thereby balancing image quality improvement with reduced motion blur and faster processing.
2Illumination intensity
If multiple images are captured and merged to improve low-light quality, then the processing complexity increases, but the image quality in low-light conditions improves
Solution Approach 1:
The patent applies the extraction principle by separating the determination of the merging parameter from the actual merging process. The processor first extracts and analyzes information from the plurality of captured images to determine the optimal merging parameter, then applies this parameter in the merging step. This separation simplifies the overall processing complexity by breaking down the complex task into manageable stages with clear objectives.
Solution Approach 2:
By performing the determination of merging parameters as a preliminary action before the actual image merging, the patent reduces processing complexity during the critical merging phase. The preliminary analysis and parameter determination stage prepares all necessary information in advance, allowing the merging operation to proceed more efficiently with pre-determined parameters rather than requiring complex real-time calculations.
3Illumination intensity
If multiple images are captured and merged to improve low-light quality, then the time consumption increases, but the image quality in low-light conditions improves
Solution Approach 1:
The patent reduces time consumption by performing preliminary determination of merging parameters before the actual image merging process. This preliminary action prepares all necessary information and parameters in advance, so that when the merging operation needs to be executed, it can proceed efficiently with pre-determined parameters, reducing the overall time required for low-light image processing.
Solution Approach 2:
The dynamic determination of merging parameters based on the specific characteristics of captured images allows the system to optimize processing time for each scenario. By adaptively adjusting parameters rather than using fixed conservative settings, the system can achieve good results faster, reducing the number of iterations or processing steps needed.
Data Source
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AI summary
This application provides a photographing method and a related device thereof, and relates to the field of image processing. The photographing method includes: determining a memory occupation amount for a quantity of an xth time of photographing; when the memory occupation amount is less than a first memory threshold, determining a level-x processing algorithm as a first photographing algorithm, and determining a level-x processing frame quantity as a first frame quantity; when the memory occupation amount is greater than or equal to the first memory threshold but less than a second memory threshold, determining the level-x processing algorithm as a second photographing algorithm, and determining the level-x processing frame quantity as a second frame quantity; or when the memory occupation amount is greater than the second memory threshold, determining the level-x processing algorithm as a third photographing algorithm, and determining the level-x processing frame quantity as a third frame quantity; processing the level-x processing frame quantity in a raw image by using the level-x processing algorithm to obtain a corresponding shot image; and saving the shot image. In this application, by distinguishing the memory occupation amount, processing algorithms with different duration and/or different processing frame quantities are adaptively selected for processing. This can reduce pressure from a memory increment, and implement continuous and fast photographing.