Short-Wave Infrared Detector Sampling Correction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Short-wave infrared detectors face challenges in high-precision measurement due to nonlinear sampling results from Fuller and ramp sampling algorithms, which do not account for the impact of the sampling process on integrating capacitor power, leading to system errors, especially under long integrating times.
Innovation Solution
A method and system that corrects system errors by determining a correction coefficient sequence based on the integrating and sampling capacitors, applying multiplication correction to images, and performing line fitting to obtain accurate algorithm output values, optimizing sampling for short-wave infrared detectors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If Fuller sampling or ramp sampling is used for multiple integrating readout, then the readout noise can be reduced, but system errors increase due to nonlinear sampling results
Solution Approach 1:
The patent transforms the nonlinear sampling results into linear results by applying a correction coefficient sequence. The correction coefficients are calculated based on the integrating time, sampling interval, and capacitor characteristics, converting the nonlinear relationship into a linear one through parameter transformation and mathematical correction.
2Reliability
If the number of sampling times is increased to improve signal-to-noise ratio, then readout noise is reduced, but the difference between actual output and ideal output increases
Solution Approach 1:
The patent introduces a feedback mechanism where the actual sampling process characteristics are measured and used to generate correction coefficients. These coefficients are then applied to compensate for the deviation between actual and ideal output, creating a closed-loop correction system that maintains accuracy even with multiple sampling operations.
3Ease of operation
If conventional correlated double sampling is used, then the readout process is simple, but it cannot eliminate readout noise well under ultra-long integrating time
Solution Approach 1:
The patent transitions from the static conventional CDS method to a dynamic multiple integrating readout approach. The system dynamically performs multiple sampling operations during the integrating period and applies dynamic correction coefficients that adapt to the actual sampling process, enabling effective readout noise elimination under ultra-long integrating time conditions.
Data Source
AI summary
A method and a system for optimizing sampling of short-wave infrared detector relate to the technical field of image processing. The method includes: enabling the multiple integrating readout function of the short-wave infrared detector; performing n integrating imaging on a target region by using a multiple integrating readout camera, subtracting a first frame image from all images to obtain n images within one integrating period; determining the correction coefficient sequence based on the integrating capacitor, the sampling capacitor, and the sampling sequence; carrying out multiplication correction respectively on the n images in sequence according to a one-to-one correspondence mode of the sampling sequence of the n images and the correction coefficient sequence order of the n images to obtain n corrected images; and performing line fitting on the corrected n images to obtain the algorithm output values for each pixel of the processed images.