Feature-Point Image Fusion for Low-Light Brightness and Clarity
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Solution Overview
Problem
Capturing images in low-luminance environments often results in difficulty recognizing objects due to motion blur from increased exposure time and limited effectiveness of image processing in enhancing brightness.
Innovation Solution
An image fusion method that transforms image frames based on feature points to align them with predefined reference points, minimizing motion blur by combining these transformed frames to improve brightness and clarity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If exposure time is increased to improve brightness in low-luminance environments, then image brightness is improved, but motion blur occurs when the object moves
Solution Approach 1:
The system performs preliminary actions by capturing multiple image frames at different exposure times before final processing. By pre-capturing a series of frames with varying exposure durations, the system prepares multiple candidate images that can be later combined to achieve both high brightness and high clarity, avoiding the need to choose between the two extremes in a single capture.
Solution Approach 2:
The system dynamically adjusts exposure time across multiple captured frames, using short exposure for clear images and long exposure for bright images. By dynamically varying the exposure parameter and then adaptively combining the resulting frames based on their respective quality characteristics, the system resolves the contradiction between brightness and clarity.
2Illumination intensity
If image processing is performed to adjust brightness, then image brightness is improved, but the effectiveness is limited in showing the object clearly
Solution Approach 1:
The system merges multiple image frames with different exposure characteristics through adaptive combination. By combining a short-exposure frame (high clarity) and a long-exposure frame (high brightness) using weighting algorithms, the system achieves both improved brightness and maintained object recognition accuracy, overcoming the limitations of single-frame processing.
Solution Approach 2:
The system introduces an intermediary processing stage that evaluates multiple captured frames and selectively combines them. This intermediary step analyzes the quality metrics of each frame and uses adaptive weighting to merge them, serving as a mediator between the conflicting requirements of brightness enhancement and clarity preservation.
3Manufacturing precision
If multiple image frames are captured and combined, then brightness and clarity are improved, but processing complexity increases
Solution Approach 1:
The system applies partial action by selectively processing only the most relevant frames from the captured sequence. Instead of uniformly processing all frames, it identifies and focuses computational resources on frames with optimal characteristics (e.g., best focus, best exposure), reducing unnecessary processing while maintaining high image quality.
Solution Approach 2:
The system changes processing parameters dynamically based on frame quality assessment. By adjusting weighting factors, combination algorithms, and processing intensity according to the specific characteristics of each captured frame, the system optimizes processing efficiency while achieving high-quality output, thereby managing complexity effectively.
Data Source
AI summary
Disclosed is an image fusion method and apparatus. The fusion method includes detecting first feature points of an object in a first image frame from the first image frame; transforming the first image frame based on the detected first feature points and predefined reference points to generate a transformed first image frame; detecting second feature points of the object in a second image frame from the second image frame; transforming the second image frame based on the detected second feature points and the predefined reference points to generate a transformed second image frame; and generating a combined image by combining the transformed first image frame and the transformed second image frame.