Focus-Based Shuttering for High Frame Rate Imaging
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Solution Overview
Problem
Current imaging technologies face limitations in capturing high-quality images at high frame rates due to the bottlenecks in global shutter methods and spatial distortions in rolling shutter methods, which result in congestion, reduced frame rates, and blurring effects.
Innovation Solution
The implementation of focus-based shuttering techniques, where blur metrics are calculated for each pixel and used to control the shuttering and digitization rates of individual pixel sensors, allowing for prioritization of high-blur regions for faster sampling and low-blur regions for longer exposure times, thereby enhancing image clarity and reducing motion blur.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If global shutter method is used to capture images simultaneously across all pixel sensors, then image quality and spatial accuracy are improved, but frame rate is reduced due to processing congestion
Solution Approach 1:
The patent divides the imaging sensor into multiple regions (e.g., first region and second region) that can be processed independently. By segmenting the sensor array, different regions can be read out simultaneously through separate pathways, eliminating the serial processing bottleneck and enabling higher frame rates while maintaining global shutter image quality
Solution Approach 2:
The patent introduces a spatial dimension to the readout process by implementing multiple independent readout pathways across the sensor array. Instead of processing all pixels through a single serial pathway, the system uses parallel readout channels that operate simultaneously, effectively adding a dimensional aspect to the data flow and enabling higher frame rates
2Productivity
If rolling shutter method is used to increase frame rate by processing pixel sensors sequentially, then productivity is improved, but spatial distortions and blurring effects are introduced
Solution Approach 1:
The patent segments the sensor into multiple regions with independent readout capabilities. This allows simultaneous capture and processing of multiple regions within a single exposure period, achieving high frame rates without the sequential processing delays that cause rolling shutter distortions
Solution Approach 2:
The system uses feedback mechanisms to dynamically adjust readout priorities and timing based on detected motion or scene characteristics. This enables the system to maintain high frame rates while compensating for motion-induced distortions by adjusting the readout sequence based on real-time scene analysis
3Stability of the object's composition
If all pixel sensors are processed at the same rate, then uniformity is maintained, but high-blur regions cannot be captured at higher sampling rates to reduce motion blur
Solution Approach 1:
The patent implements differential processing where different regions of the sensor array are processed at different rates based on their specific needs. High-motion regions are sampled at higher rates to capture motion details, while static regions use lower sampling rates, optimizing overall image quality and reducing motion blur in critical areas
Solution Approach 2:
The system dynamically adjusts readout rates and processing priorities based on real-time scene analysis. Motion detection algorithms identify regions requiring higher sampling rates, and the readout system adapts its timing and sequence accordingly, enabling variable sampling rates across different sensor regions within the same exposure
Data Source
AI summary
Blur metrics may be calculated for each of the image pixels of a digital image of a scene captured using an imaging device. The blur metrics may be indicative of the level of blur expressed in the digital image, and a blur image representative of the blur metrics may be generated. Subsequently, when another digital image is to be captured using the imaging device, pixel sensors corresponding to high blur metrics may be digitized at a high level of priority, or at a high rate, compared to pixel sensors corresponding to low blur metrics, which may be digitized at a low level of priority, or at a low rate. The blur images may be updated based on changes in blur observed in subsequent images, and different pixel sensors may be digitized at higher or lower levels of priority, or at higher or lower rates, based on the changes in blur.