Methods, apparatus, and systems for super resolution of LIDAR data sets
View Patent ↗Light detection and ranging (LIDAR) imaging systems, method, and computer readable media for generating super-resolved images are described. Super-resolved images are generated by obtaining data sets of cloud points representing multiple views of an object where the views have a view shift, enhancing the views by duplicating cloud points within each of the data sets, compensating for the view shift using the enhanced views, identifying valid cloud points, and generating a super-resolved image of the object by integrating valid cloud points within the compensated, enhanced views.
1. A light detection and ranging (LIDAR) imaging method comprising:
obtaining data sets of cloud points representing each of a plurality of views of an object, the plurality of views having at least one view shift;
enhancing the plurality of views by duplicating cloud points within each of the obtained data sets;
compensating for the at least one view shift using the enhanced plurality of views by;
shifting one of the enhanced plurality of views with respect to an other one of the enhanced plurality of views by a plurality of different shift amounts,
determining focus measurements between the one of the enhanced plurality of views and the other one of the enhanced plurality of views for each of the plurality of different shift amounts,
registering a compensation shift amount from the plurality of different shift amounts corresponding to a maximum one of the determined focus measurements, and
shifting the one of the enhanced plurality of views by the registered compensation shift amount;
identifying valid cloud points; and
generating a super-resolved image of the object from the compensated, enhanced plurality of views with a processor by integrating the valid cloud points located at each of a plurality of spatial coordinates within the compensated, enhanced plurality of views.
2. The method of claim 1 , wherein the data sets are stored in a computer memory and the obtaining comprises:
retrieving the data sets from the memory.
3. The method of claim 1 , wherein the plurality of views are rectangular and the enhancing step comprises:
duplicating the cloud points within each of the data sets by a constant amount.
4. The method of claim 1 , wherein the plurality of views are elliptical and the enhancing step comprises:
duplicating the cloud points within each of the data sets by an amount that varies from the center to the periphery of each of the plurality of views.
5. The method of claim 1 , wherein the at least one view shift is known and the compensating comprises:
shifting at least one of the enhanced plurality of views by the known shift amount.
6. The method of claim 1 , wherein the identifying comprises:
identifying the valid cloud points within the enhanced plurality of views.
7. The method of claim 1 , wherein the identifying step comprises:
identifying invalid cloud points to identify the valid cloud points.
8. The method of claim 1 , wherein the generating comprises:
integrating valid cloud points by averaging the valid cloud points within the compensated, enhanced plurality of views.
9. The method of claim 1 , wherein the generating step comprises:
integrating valid cloud points by determining the minimum of the valid cloud points within the compensated, enhanced plurality of views.
10. The method of claim 1 , wherein the generating step comprises:
integrating valid cloud points by determining the median of the valid cloud points within the compensated, enhanced plurality of views.
11. The method of claim 1 , further comprising:
presenting the super-resolved image on a display.
12. A light detection and ranging (LIDAR) imaging system comprising:
a memory including data sets of cloud points representing each of a plurality of views of an object, the plurality of views having at least one view shift;
a display; and
a processor coupled to the memory and the display, the processor configured to obtain the data sets from the memory, enhance the plurality of views by duplicating cloud points within each of the obtained data sets, compensate for the at least one view shift using the enhanced plurality of views, identify valid cloud points, generate a super-resolved image of the object from the compensated, enhanced plurality of views with a processor by integrating the valid cloud points located at each of a plurality of spatial coordinates within the compensated, enhanced plurality of views, and present the super-resolved image on the display;
wherein the processor is configured to shift one of the enhanced plurality of views with respect to another one of the enhanced plurality of views by a plurality of different shift amounts, determine focus measurements between the one of the enhanced plurality of views and the other one of the enhanced plurality of views for each of the plurality of different shift amounts, register a compensation shift amount from the plurality of different shift amounts corresponding to a maximum one of the determined focus measurements; and shift the one of the enhanced plurality of views by the registered compensation shift amount in order to compensate for the at least one view shift.
13. The system of claim 12 , wherein the plurality of views are rectangular and the processor is configured to enhance the plurality of views by duplicating the cloud points within each of the data sets by a constant amount.
14. The system of claim 12 , wherein the plurality of views are elliptical and the processor is configured to enhance the plurality of views by duplicating the cloud points within each of the data sets by an amount that varies from the center to the periphery of each of the plurality of views.
15. The system of claim 12 , wherein the processor is configured to generate the super-resolved image by integrating valid cloud points by averaging the valid cloud points within the compensated, enhanced plurality of views.
16. A non-transitory computer readable medium including instructions for configuring a computer to perform a light detection and ranging (LIDAR) imaging method, the method comprising:
obtaining data sets of cloud points representing each of a plurality of views of an object, the plurality of views having at least one view shift;
enhancing the plurality of views by duplicating cloud points within each of the obtained data sets;
compensating for the at least one view shift using the enhanced plurality of views by;
shifting one of the enhanced plurality of views with respect to an other one of the enhanced plurality of views by a plurality of different shift amounts,
determining focus measurements between the one of the enhanced plurality of views and the other one of the enhanced plurality of views for each of the plurality of different shift amounts,
registering a compensation shift amount from the plurality of different shift amounts corresponding to a maximum one of the determined focus measurements, and
shifting the one of the enhanced plurality of views by the registered compensation shift amount,
identifying valid cloud points; and
generating a super-resolved image of the object from the compensated, enhanced plurality of views with a processor by integrating the valid cloud points located at each of a plurality of spatial coordinates within the compensated, enhanced plurality of views.
17. The non-transitory computer readable medium of claim 16 , wherein the plurality of views are rectangular and the enhancing step comprises:
duplicating the cloud points within each of the data sets by a constant amount.
18. The non-transitory computer readable medium of claim 16 , wherein the plurality of views are elliptical and the enhancing step comprises:
duplicating the cloud points within each of the data sets by an amount that varies from the center to the periphery of each of the plurality of views.
19. The non-transitory computer readable medium of claim 16 , wherein the generating comprises:
integrating valid cloud points by averaging the valid cloud points within the compensated, enhanced plurality of views.