Structured Differential Motion Estimation for HDR LED Flicker Detection
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Solution Overview
Problem
Existing image processing systems struggle to differentiate between LED flicker and moving objects in HDR imagery, leading to inaccurate image capture and recognition, particularly in environments with both LED light sources and moving objects, due to the complexity of pinpointing LED flicker location and limitations of current LED flicker mitigation solutions.
Innovation Solution
A structured differential motion estimation algorithm using spatially multiplexed image sensors and a four-step workflow to distinguish between LED flickers and moving objects by analyzing pixel intensity patterns, including differential calculation, motion position estimation, structured motion search, and motion weighting estimation, to generate optimal HDR images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If LED flicker mitigation is applied to all pixels, then LED flicker artifacts are reduced, but moving objects become blurred due to incorrect processing
Solution Approach 1:
The patent segments the image into different regions: LED flicker regions and moving object regions. By calculating motion vectors and comparing them against LED flicker characteristics, the system identifies which pixels correspond to LED sources and which correspond to moving objects. This segmentation allows different processing strategies to be applied to different regions, resolving the contradiction between mitigating LED flicker and preserving moving object clarity.
Solution Approach 2:
The patent applies local quality by treating different spatial regions of the image differently. Instead of uniformly applying LED flicker mitigation to all pixels, the system selectively applies processing based on local motion characteristics. Pixels identified as part of moving objects receive different treatment than pixels identified as LED sources, thereby preserving moving object detail while still mitigating LED flicker in appropriate regions.
2Reliability
If camera exposure is synchronized with LED PWM frequency, then LED flicker artifacts are eliminated, but the system becomes complex and not universally applicable
Solution Approach 1:
The patent replaces the mechanical/synchronization-based approach with a computational/image-processing-based approach. Instead of requiring hardware synchronization between camera exposure and LED PWM frequency, the system uses post-capture image processing to identify and mitigate LED flicker artifacts. This substitution eliminates the need for complex synchronization mechanisms while achieving similar or better results.
Solution Approach 2:
The patent changes the approach from controlling exposure timing parameters to analyzing and processing image data parameters. By working with captured image data rather than controlling camera exposure timing, the system avoids the complexity of synchronization while still能够有效 addressing LED flicker. The motion vector calculation and comparison parameters enable flexible, parameter-driven LED flicker mitigation without hardware synchronization.
3Measurement precision
If motion estimation is performed on all pixels, then moving objects are accurately tracked, but processing time increases significantly
Solution Approach 1:
The patent applies segmentation by first performing motion estimation on a subset of pixels or using efficient algorithms to identify regions of interest. By focusing computational resources on areas with significant motion or potential LED flicker, rather than uniformly processing all pixels, the system maintains tracking accuracy while reducing overall processing time.
Solution Approach 2:
The patent implements partial action by performing full motion estimation only where necessary (e.g., in regions with detected changes or potential LED sources) rather than on the entire image. This selective approach applies sufficient processing to maintain accuracy in critical regions while avoiding excessive processing in static or less important areas, thereby optimizing the balance between tracking accuracy and processing time.
Data Source
AI summary
This application describes an image processing system and method for LED Flicker Mitigation (LFM). An example method involves capturing multiple frames of a scene using an image sensor configured with various exposure settings. Based on the pixel values in the frames, the edges of a changing object may be identified in each frame, which could be a moving object or an LED source. It then determines the object's moving path between two frames captured with different exposure settings. The amount of movement of the changing object is calculated based on this moving path. The system then estimates the likelihood of the changing object being either the moving object or the LED source, based on the amount of movement. Finally, an image of the scene is generated using the captured frames by performing High Dynamic Range (HDR) fusion and LFM, taking into account the likelihood of the changing object's identity.