System and method for reducing stray light interference in optical systems
Disclosed herein are systems, methods, and computer program products for reducing optical interference in an optical sensor. The methods comprise: detecting, by an optical sensor device comprising a plurality of pixel sensors, a signal with a reflected light component and a stray light component; estimating, by a processor, a stray light intensity in each pixel of the plurality of pixel sensors using a measured mapping of an intensity of stray light relative to an intensity of reflected light, wherein the measured mapping is derived from the measured intensities associated with all pixel sensors of the optical sensor device; adjusting, by the processor, a noise probability for the signal using the estimated stray light intensity and an unbiased noise intensity; and adjusting, by the processor, a signal confidence score using the adjusted noise probability.
1. A method for reducing optical interference in an optical sensor comprising:
detecting, by an optical sensor device comprising a plurality of pixel sensors, a signal with a reflected light component and a stray light component;
estimating, by a processor, a stray light intensity in each pixel of the plurality of pixel sensors using a measured mapping of an intensity of stray light relative to an intensity of reflected light, wherein the measured mapping is derived from the measured intensities associated with all pixel sensors of the optical sensor device;
adjusting, by the processor, a noise probability for the signal using the estimated stray light intensity and an unbiased noise intensity; and
adjusting, by the processor, a signal confidence score using the adjusted noise probability.
2. The method according to claim 1 , further comprising using the adjusted signal confidence score to control autonomous operations of a robot.
3. The method according to claim 1 , further comprising classifying points in a point cloud as bloom points, wherein the point cloud is generated based on outputs from the optical sensor device.
4. The method according to claim 3 , wherein the classifying comprises identifying points of the point cloud that have range values within a given range tolerance defined by the minimum range and maximum range associated with a pixel considered to possibly be associated with an object causing bloom.
5. The method according to claim 4 , wherein the classifying further comprises filtering the point using heuristics or confidence thresholding.
6. The method according to claim 1 , wherein the noise probability is adjusted by adding the estimated stray light intensity to the unbiased noise intensity or by multiplying a first number derived using the unbiased noise intensity and a second number derived using the estimated stray light intensity.
7. The method according to claim 1 , wherein the adjusted signal confidence score is a function of a span count and a trial count in addition to the adjusted noise probability.
8. The method according to claim 1 , further comprising adjusting an intensity of the reflected light using the adjusted noise probability and a photon detection efficiency.
9. The method according to claim 1 , further comprising filtering points from a point cloud based on a comparison of the adjusted signal confidence score to a threshold value.
10. The method according to claim 1 , wherein the measured mapping comprises a point spread function obtained by emitting a reference light signal towards a particular pixel sensor and measuring an intensity of light detected by all other ones of the pixel sensors.
11. A system, comprising:
an optical sensor device comprising a plurality of pixel sensors and configured to detect a signal with a reflected light component and a stray light component;
a processor; and
a non-transitory computer-readable storage medium comprising programming instructions that are configured to cause the processor to implement a method for operating a system, wherein the programming instructions comprise instructions to:
estimate a stray light intensity in each pixel of the plurality of pixel sensors using a measured mapping of an intensity of stray light relative to an intensity of reflected light, wherein the measured mapping is derived from the measured intensities associated with all pixel sensors of the optical sensor device;
adjust a noise probability for the signal using the estimated stray light intensity and an unbiased noise intensity; and
adjust a signal confidence score using the adjusted noise probability.
12. The system according to claim 11 , wherein the programming instructions further comprise instructions to classify points in a point cloud as bloom points, the point cloud being generated based on outputs from the optical sensor device.
13. The system according to claim 12 , wherein identified points have range values within a given range tolerance defined by the minimum range and maximum range associated with a pixel considered to possibly be associated with an object causing bloom.
14. The system according to claim 13 , wherein the identified point are filtered using heuristics or confidence thresholding.
15. The system according to claim 11 , wherein the noise probability is adjusted by adding the estimated stray light intensity to the unbiased noise intensity or by multiplying a first number derived using the unbiased noise intensity and a second number derived using the estimated stray light intensity.
16. The system according to claim 11 , wherein the adjusted signal confidence score is a function of a span count and a trial count in addition to the adjusted noise probability.
17. The system according to claim 11 , wherein the programming instructions further comprise instructions to adjust an intensity of the reflected light using the adjusted noise probability and a photon detection efficiency.
18. The system according to claim 11 , wherein the programming instructions further comprise instructions to filter points from a point cloud based on a comparison of the adjusted signal confidence score to a threshold value.
19. The system according to claim 11 , wherein the measured mapping comprises a point spread function obtained by emitting a reference light signal towards a particular pixel sensor and measuring an intensity of light detected by all other ones of the pixel sensors.
20. A non-transitory computer-readable medium that stores instructions that, when executed by at least one computing device, will cause the at least one computing device to perform operations comprising:
estimating, by a processor, a stray light intensity in each pixel of the plurality of pixel sensors using a measured mapping of an intensity of stray light relative to an intensity of reflected light, wherein the measured mapping is derived from measured intensities associated with all pixel sensors of the optical sensor device;
adjusting a noise probability for the signal using the estimated stray light intensity and an unbiased noise intensity; and
adjusting a signal confidence score using the adjusted noise probability.