Image Sharpness Selection via Rapid Sequential Capture
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Solution Overview
Problem
Digital images often become blurred due to camera or object movement during low-light photography, and existing stabilization methods like flashes and tripods are not always effective or readily available, leading to time-consuming manual review of captured images for quality.
Innovation Solution
An image capturing device with a processing device and module that rapidly captures multiple images, analyzes focus quality using a ranking algorithm, and selects the sharpest image for storage or display, automatically eliminating blurry ones.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If multiple images are captured in sequence to select the sharpest one, then image quality is improved, but loss of time increases due to capturing and processing multiple images
Solution Approach 1:
The system performs preliminary capture of multiple images in rapid succession before the subject moves significantly, then automatically analyzes and selects the sharpest image. This preliminary action of capturing multiple frames upfront eliminates the need for manual review of multiple images, resolving the contradiction by automating the selection process while maintaining image quality.
Solution Approach 2:
The patent replaces the manual mechanical process of reviewing images one by one on a display with an automated computational system that analyzes sharpness metrics and selects the best image programmatically. This substitution eliminates the time-consuming manual review process while ensuring consistent selection of the sharpest image.
2Measurement precision
If manual review of captured images is performed to determine quality, then image selection accuracy is improved, but loss of time increases significantly
Solution Approach 1:
The system replaces manual visual inspection with an automated image processing algorithm that calculates sharpness metrics (such as gradient magnitude, frequency domain analysis, or edge detection) to objectively assess image quality. This computational approach maintains high assessment accuracy while eliminating the time required for manual review of each image.
Solution Approach 2:
The system performs self-assessment of image quality by automatically analyzing its own captured images using embedded processing algorithms. The device independently determines which image is sharpest without requiring external human intervention, thus maintaining precision while dramatically reducing the time investment required.
3Manufacturing precision
If flash is used to reduce exposure time and minimize blur, then image sharpness is improved, but adaptability decreases when flash is not available or permitted
Solution Approach 1:
The system provides a universal solution that works regardless of lighting conditions or flash availability. By capturing multiple images in rapid succession and selecting the sharpest one through automated analysis, the system achieves sharp images in both flash and non-flash scenarios, adapting to various conditions without requiring flash to be the primary solution.
Solution Approach 2:
The system changes the parameter of capture rate (capturing multiple images in quick succession) rather than relying on flash duration. This parameter change allows the system to achieve sharp images through temporal sampling rather than through flash illumination, maintaining adaptability across different lighting conditions and restrictions.
4Manufacturing precision
If tripod is used to stabilize camera, then image sharpness is improved, but ease of operation decreases and device complexity increases
Solution Approach 1:
The patent replaces the mechanical stabilization system (tripod) with a computational approach that captures multiple images in rapid succession and selects the sharpest one through automated analysis. This substitution maintains image sharpness while eliminating the need for external stabilization equipment, greatly improving ease of operation.
Solution Approach 2:
The system provides self-stabilization through rapid sequential capture and automated selection of the sharpest frame. Rather than requiring external mechanical support, the device uses its own processing capabilities to identify and select the best image from multiple captures, maintaining sharpness while improving portability and ease of use.
Data Source
AI summary
A method, apparatus, and system are disclosed for selecting quality images from multiple captured images. One embodiment is an image capturing system. The system includes hardware for capturing a plurality of consecutive images and a processor for determining a quality indication for the consecutive images and for selecting one of the consecutive images based on the quality indication.