Noise reduction in light detection and ranging based imaging
IPC분류정보
국가/구분
United States(US) Patent
등록
국제특허분류(IPC7판)
G06K-009/00
G06K-009/62
G01S-017/10
G01S-017/89
G01S-007/487
G01S-007/486
출원번호
US-0220131
(2011-08-29)
등록번호
US-8913784
(2014-12-16)
발명자
/ 주소
Collard, Corey J.
Goodman, Vernon R.
출원인 / 주소
Raytheon Company
대리인 / 주소
Burns & Levinson LLP
인용정보
피인용 횟수 :
0인용 특허 :
40
초록▼
A method, in accordance with particular embodiments, includes receiving voxel data for a plurality of voxels. Each voxel is associated with a unique volume of space associated with a geographic area. The voxel data for each respective voxel includes one or more values based on one or more reflection
A method, in accordance with particular embodiments, includes receiving voxel data for a plurality of voxels. Each voxel is associated with a unique volume of space associated with a geographic area. The voxel data for each respective voxel includes one or more values based on one or more reflections from one or more light pulses from a LIDAR system. The method further includes identifying noise values from among the one or more values for each respective voxel. The method additionally includes determining a baseline threshold comprising a static value that is uniform for each of the voxels. The method additionally includes determining a dynamic threshold that varies between the voxels and is based on the identified noise values. The method further includes applying the baseline and dynamic thresholds to the voxel data to generate filtered voxel data. The method also includes generating a three-dimensional image based on the filtered voxel data.
대표청구항▼
1. A method comprising: receiving voxel data for each of a plurality of voxels, each voxel associated with a unique volume of space associated with a geographic area, the voxel data for each respective voxel comprising one or more values based on one or more reflections from one or more light pulses
1. A method comprising: receiving voxel data for each of a plurality of voxels, each voxel associated with a unique volume of space associated with a geographic area, the voxel data for each respective voxel comprising one or more values based on one or more reflections from one or more light pulses from a light detection and ranging (LIDAR) system;identifying noise values from among the one or more values for each respective voxel;determining a baseline threshold comprising a static value that is uniform for each of the plurality of voxels;determining a dynamic threshold that varies between the plurality of voxels, the dynamic threshold based on the identified noise values, wherein the variation of the dynamic threshold between the plurality of voxels corresponds to spatial variations inherent in the LIDAR system;applying the baseline threshold and the dynamic threshold to the voxel data to generate filtered voxel data;generating a three-dimensional image based on the filtered voxel data;determining an along-path histogram based on noise values from among the one or more values for each respective voxel along a flight path of the LIDAR system;determining a cross-path histogram, the cross-path histogram based on noise values from among the one or more values for each respective voxel perpendicular to the flight path of the LIDAR system; andmultiplying the along-path histogram by the cross-path histogram. 2. The method of claim 1, wherein: the voxels are arranged in a three-dimensional pattern comprising a plurality of rows, columns, and posts arranged orthogonally to one another, wherein: each row of the plurality of rows comprises a plurality of voxels arranged substantially parallel to the flight path;each column of the plurality of columns comprises a plurality of voxels arranged substantially perpendicular to the flight path; andeach post of the plurality of posts comprises a plurality of voxels arranged in a substantially vertical stack; anddetermining an along-path histogram comprises, for each column of voxels, determining a total noise count based on a sum of noise from a plurality of posts from a plurality of rows from a respective column. 3. The method of claim 1, wherein: the voxels are arranged in a three-dimensional pattern comprising a plurality of rows, columns, and posts arranged orthogonally to one another, wherein: each row of the plurality of rows comprises a plurality of voxels arranged substantially parallel to the flight path;each column of the plurality of columns comprises a plurality of voxels arranged substantially perpendicular to the flight path; andeach post of the plurality of posts comprises a plurality of voxels arranged in a substantially vertical stack; anddetermining a cross-path histogram comprises, for each row of voxels, determining a total noise count based on a sum of noise from a plurality of posts from a plurality of columns from a respective row. 4. The method of claim 1, wherein determining a dynamic threshold comprises: determining a noise count for each post of a plurality of posts, each post comprising a vertical stack of voxels;filtering the noise count for each voxel through a low-pass filter; andscaling the filtered noise count for each voxel. 5. The method of claim 1, wherein determining a baseline threshold comprises determining a baseline threshold based on a percentage of the number of light pulses per post, each post comprising a vertical stack of voxels. 6. The method of claim 1, further comprising correcting a photon intensity of the three-dimensional image. 7. An apparatus comprising: an interface configured to receive voxel data for each of a plurality of voxels, each voxel associated with a unique volume of space associated with a geographic area, the voxel data for each respective voxel comprising one or more values based on one or more reflections from one or more light pulses from a light detection and ranging (LIDAR) system; anda processor coupled to the interface and configured to: identify noise values from among the one or more values for each respective voxel;determine a baseline threshold comprising a static value that is uniform for each of the plurality of voxels;determine a dynamic threshold that varies between the plurality of voxels, the dynamic threshold based on the identified noise values, wherein the variation of the dynamic threshold between the plurality of voxels corresponds to spatial variations inherent in the LIDAR system;apply the baseline threshold and the dynamic threshold to the voxel data to generate filtered voxel data;generate a three-dimensional image based on the filtered voxel data;determine an along-path histogram based on noise values from among the one or more values for each respective voxel along a flight path of the LIDAR system;determine a cross-path histogram, the cross-path histogram based on noise values from among the one or more values for each respective voxel perpendicular to the flight path of the LIDAR system; andmultiply the along-path histogram by the cross-path histogram. 8. The apparatus of claim 7, wherein: the voxels are arranged in a three-dimensional pattern comprising a plurality of rows, columns, and posts arranged orthogonally to one another, wherein: each row of the plurality of rows comprises a plurality of voxels arranged substantially parallel to the flight path;each column of the plurality of columns comprises a plurality of voxels arranged substantially perpendicular to the flight path; andeach post of the plurality of posts comprises a plurality of voxels arranged in a substantially vertical stack; andthe processor configured to determine an along-path histogram is further configured to, for each column of voxels, determine a total noise count based on a sum of noise from a plurality of posts from a plurality of rows from a respective column. 9. The apparatus of claim 7, wherein: the voxels are arranged in a three-dimensional pattern comprising a plurality of rows, columns, and posts arranged orthogonally to one another, wherein each row of the plurality of rows comprises a plurality of voxels arranged substantially parallel to the flight path;each column of the plurality of columns comprises a plurality of voxels arranged substantially perpendicular to the flight path; andeach post of the plurality of posts comprises a plurality of voxels arranged in a substantially vertical stack; andthe processor configured to determine a cross-path histogram is further configured to, for each row of voxels, determine a total noise count based on a sum of noise from a plurality of posts from a plurality of columns from a respective row. 10. The apparatus of claim 7, wherein the processor configured to determine a dynamic threshold is further configured to: determine a noise count for each post of a plurality of posts, each post comprising a vertical stack of voxels;filter the noise count for each voxel through a low-pass filter; andscale the filtered noise count for each voxel. 11. The apparatus of claim 7, wherein the processor configured to determine a baseline threshold is further configured to determine a baseline threshold based on a percentage of the number of light pulses per post, each post comprising a vertical stack of voxels. 12. The apparatus of claim 7, wherein the processor is further configured to correct a photon intensity of the three-dimensional image. 13. Logic embodied on a tangible non-transitory computer readable medium, that when executed is configured to: receive voxel data for each of a plurality of voxels, each voxel associated with a unique volume of space associated with a geographic area, the voxel data for each respective voxel comprising one or more values based on one or more reflections from one or more light pulses from a light detection and ranging (LIDAR) system;identify noise values from among the one or more values for each respective voxel;determine a baseline threshold comprising a static value that is uniform for each of the plurality of voxels;determine a dynamic threshold that varies between the plurality of voxels, the dynamic threshold based on the identified noise values, wherein the variation of the dynamic threshold between the plurality of voxels corresponds to spatial variations inherent in the LIDAR system;apply the baseline threshold and the dynamic threshold to the voxel data to generate filtered voxel data;generate a three-dimensional image based on the filtered voxel data;determine an along-path histogram based on noise values from among the one or more values for each respective voxel along a flight path of the LIDAR system;determine a cross-path histogram, the cross-path histogram based on noise values from among the one or more values for each respective voxel perpendicular to the flight path of the LIDAR system; andmultiply the along-path histogram by the cross-path histogram. 14. The logic of claim 13, wherein: the voxels are arranged in a three-dimensional pattern comprising a plurality of rows, columns, and posts arranged orthogonally to one another, wherein: each row of the plurality of rows comprises a plurality of voxels arranged substantially parallel to the flight path;each column of the plurality of columns comprises a plurality of voxels arranged substantially perpendicular to the flight path; andeach post of the plurality of posts comprises a plurality of voxels arranged in a substantially vertical stack; andthe executed logic configured to determine an along-path histogram is, when executed, further configured to, for each column of voxels, determine a total noise count based on a sum of noise from a plurality of posts from a plurality of rows from a respective column. 15. The logic of claim 13, wherein: the voxels are arranged in a three-dimensional pattern comprising a plurality of rows, columns, and posts arranged orthogonally to one another, wherein; each row of the plurality of rows comprises a plurality of voxels arranged substantially parallel to the flight path;each column of the plurality of columns comprises a plurality of voxels arranged substantially perpendicular to the flight path; andeach post of the plurality of posts comprises a plurality of voxels arranged in a substantially vertical stack; andthe executed logic configured to determine a cross-path histogram is, when executed, further configured to, for each row of voxels, determine a total noise count based on a sum of noise from a plurality of posts from a plurality of columns from a respective row. 16. The logic of claim 13, wherein the executed logic configured to determine a dynamic threshold is, when executed, further configured to: determine a noise count for each post of a plurality of posts, each post comprising a vertical stack of voxels;filter the noise count for each voxel through a low-pass filter; andscale the filtered noise count for each voxel. 17. The logic of claim 13, wherein the executed logic configured to determine a baseline threshold is, when executed, further configured to determine a baseline threshold based on a percentage of the number of light pulses per post, each post comprising a vertical stack of voxels.
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