Sub-frame Jitter Compensation Using Digital Pixel Reassignment
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Legacy analog imagers suffer from image blur and reduced modulation transfer function due to line-of-sight jitter and relative motion between optics and the focal plane array, limiting compensation to frame-by-frame basis and specific vibration frequencies.
Innovation Solution
A digital pixel imager system incorporating an array of digital pixels, an accelerometer, and a readout integrated circuit (ROIC) that assigns pulses from one pixel to another based on accelerometer data to correct for relative motion, allowing compensation across a broader frequency band.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If mechanical rigidity is increased between optics and focal plane array, then stability improves, but device complexity and cost increase
Solution Approach 1:
The system uses an accelerometer to continuously monitor vibration and motion of the imaging device, providing real-time feedback about platform instability. This feedback is processed to generate correction values that are applied to pixel count assignments, enabling dynamic compensation without requiring mechanically rigid structures.
Solution Approach 2:
The invention replaces mechanical stabilization systems (such as gimbals, vibration isolation mechanisms, or rigid mounting structures) with a digital signal processing approach. By using an accelerometer to detect motion and digitally reassigning pixel counts based on detected vibrations, the system achieves stabilization without complex mechanical components.
2Measurement precision
If frame integration period is extended, then signal-to-noise ratio improves, but motion-induced blur increases
Solution Approach 1:
The system performs preliminary measurement of platform vibration and motion during the integration period using an accelerometer. Based on this preliminary data, it pre-calculates correction values that are applied to the pixel count assignments after integration, allowing the system to maintain long integration periods while compensating for motion effects.
Solution Approach 2:
The accelerometer acts as an intermediary between the physical vibration environment and the digital image processing system. It translates mechanical vibrations into electrical signals that can be processed to generate correction values, bridging the gap between physical motion and digital compensation without requiring mechanical intervention.
3Measurement precision
If digital pixel count assignment is corrected in real-time, then image acuity improves, but processing complexity increases
Solution Approach 1:
The correction process is segmented into distinct stages: (1) accelerometer data acquisition during integration, (2) vibration signal processing and correction value generation, and (3) pixel count assignment correction after integration. This segmentation allows each stage to be optimized independently and simplifies the overall processing architecture.
Solution Approach 2:
The system changes the parameter being corrected from physical position (which would require mechanical adjustment) to digital pixel count assignment. By modifying the digital assignment values based on accelerometer data, the system achieves image acuity improvement through software processing rather than hardware complexity.
4Measurement precision
If vibration compensation is applied across broader frequency band, then image quality improves, but computational load increases
Solution Approach 1:
The system samples vibration at the accelerometer's natural sampling rate and processes correction values periodically, rather than requiring continuous high-frequency processing. This periodic approach enables compensation across a broader frequency band while maintaining manageable computational load by leveraging the inherent periodic nature of vibration signals.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system effectively reduces image blur and improves signal-to-noise ratio by reallocating counts from affected pixels, enabling compensation for motion-induced scene projection changes across a wider frequency range, thus enhancing image acuity in vibrating platforms.
Implementation Method 1
an accelerometer connected to the image detection device
Data Source
AI summary
An imaging detector includes an image detection device that includes an array of digital pixels, each digital pixel including an output that provides a pulse each time a charged stored in the digital pixel exceeds a threshold, an accelerometer connected to the image detection device, and a readout integrated circuit (ROIC) connected to the accelerometer and connected to the output of each of the digital pixels and that receives pulses from each pixel. The ROIC includes a plurality of accumulators. Each of the plurality of accumulators associated with a respective digital pixel is configured to receive a pulse from a first digital pixel of the array of digital pixels and to assign the received pulse to an accumulator associated with another digital pixel of the array based on information received from the accelerometer.