Motion-Compensated Composite Image Construction via Dynamic Frame Count
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Solution Overview
Problem
Imaging systems face challenges in producing clear images due to relative movement between the camera and the scene, requiring a balance between sufficient images for motion compensation and maintaining a high signal-to-noise ratio (SNR), which is often compromised by increased noise from multiple exposures.
Innovation Solution
A method that dynamically adjusts the number of images based on estimated motion between images, allowing for fewer images under low motion conditions to enhance SNR and more images when motion is significant to reduce blurring, by computing exposure parameters and combining earlier, later, and new images to form a motion-compensated composite image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If the number of images N is increased to provide greater motion compensation correction, then motion blurring is reduced, but noise contributions to each image increase resulting in degraded signal-to-noise ratio (SNR)
Solution Approach 1:
The patent dynamically adjusts the number of images N used in compositing based on the estimated motion magnitude between frames. When motion is large, more images are used to achieve better motion compensation; when motion is small, fewer images are used to maintain high SNR. This dynamic adaptation resolves the contradiction by optimizing the trade-off between motion compensation precision and SNR based on actual scene conditions.
Solution Approach 2:
The patent changes the parameter N (number of images) based on motion estimation results. By computing motion between images and adjusting N accordingly, the system adapts the compositing process to balance motion compensation needs against noise accumulation, thereby resolving the contradiction between these two competing requirements.
2Productivity
If the exposure time E/N for each image is reduced to capture more frames, then motion compensation capability is improved, but the signal-to-noise ratio of each individual image degrades
Solution Approach 1:
The patent dynamically determines the number of images N to use in compositing based on motion estimation. This allows the system to capture multiple frames at reduced exposure time for motion compensation while selectively using only the necessary number of frames, thereby preventing excessive noise accumulation and maintaining optimal SNR.
Solution Approach 2:
The patent captures more images than the minimum single exposure would provide, but uses only the optimal number N of these images for the final composite. This partial use of captured images allows the system to benefit from motion compensation while avoiding the noise penalty of using all captured frames.
Data Source
AI summary
A method for constructing a motion-compensated composite image of a scene includes acquiring a plurality of images of a scene over time, the plurality of images including an earlier-acquired image of the scene and a later-acquired image scene. The relative motion between the earlier and later acquired images are estimated, and an exposure parameter is computed based upon the estimated relative motion occurring between the earlier and later acquired images. A new image of the scene is acquired using the computed exposure parameter, and the earlier, later, and newly acquired images are combined to produce a motion-compensated composite image of the scene.