Mobile Camera Raw Image Selection Using Jitter Thresholds
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing photographing methods using mobile devices often result in blurry images due to user hand shaking, object movement, and focusing issues, leading to poor image sharpness and user experience.
Innovation Solution
The method involves obtaining multiple frames of images and calculating their jitter amounts using gyro data to select an image with a jitter amount within a preset threshold, ensuring the selected image meets the sharpness requirements before processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If multiple frames of images are obtained and jitter amounts are calculated to select the sharpest image, then image sharpness is improved, but processing time and computational complexity increase
Solution Approach 1:
The patent applies preliminary action by pre-obtaining N frames of images and pre-calculating their jitter amounts before the actual photographing operation. When the user triggers photo capture, the system has already prepared multiple candidate frames with their quality assessments, allowing for rapid selection of the sharpest image without real-time processing delays. This is implemented by continuously capturing preview frames and evaluating their jitter levels in advance.
Solution Approach 2:
The patent uses partial action by obtaining N frames (where N is a positive integer) instead of processing all possible frames. The system selectively captures a specific number of frames based on the jitter threshold criterion, processing only the necessary quantity to ensure image sharpness without excessive computation. This balances quality assurance with efficient resource utilization.
2Manufacturing precision
If multiple frames of images are obtained and jitter amounts are calculated to select the sharpest image, then image quality is improved, but device complexity increases
Solution Approach 1:
The patent extracts only the essential information needed for image quality assessment by calculating jitter amounts based on gyro data without processing the entire image content. The system isolates the key quality indicator (jitter amount) from the complex image data, using only the necessary computational elements to determine image sharpness. This extraction approach simplifies the processing complexity while maintaining quality improvement.
3Manufacturing precision
If N frames of images are obtained in advance, then image sharpness is improved, but memory usage and data processing load increase
Solution Approach 1:
The patent changes the parameter N (number of frames to be obtained) to control the balance between image sharpness and data volume. By adjusting N, the system can adapt to different memory constraints and processing capabilities while maintaining the core functionality of selecting the sharpest image from multiple candidates. This parameter adjustment allows flexible optimization based on available resources.
Data Source
Figure 1
Figure 2
Figure 3(A)~3(B)
AI summary
This application discloses a photographing method and an electronic device. The method includes: obtaining N frames of images in response to a first operation, where the first operation is an operation performed on a photographing control, the N frames of images are N frames of images in a preview picture that are collected by using a camera, and N is a positive integer; and determining a target image as an output raw image in a process of sequentially obtaining jitter amounts of all of the N frames of images, where the raw image is an image obtained by an electronic device by using a sensor of the camera, and the target image is an image that meets a jitter amount requirement and that is determined from the N frames of images based on the jitter amounts. In embodiments of this application, sharpness of a raw image can be ensured, thereby improving photographing experience of a user.