Method for visualization of point cloud data based on scene content

• US 20100208981A1
• Filed: 02/13/2009
• Published: 08/19/2010
• Est. Priority Date: 02/13/2009
• Status: Abandoned Application

• Current Assignee: Harris Corporation (L3Harris Technologies, Inc.)
• Original Assignee: Harris Corporation (L3Harris Technologies, Inc.)
• Inventors: Gluvna, Katie, Smith, Anthony O'Neil, Minear, Kathleen
• Application Number:
  US12/378,353
• Publication Number:
  US 20100208981A1
• Time in Patent Office: Days
• US Class Current: 382/154
• CPC Class Codes: G06T 11/001 Texturing; Colouring; Generation of texture or colour inpainting G06T5/77

Abstract

Systems and methods for associating color with spatial data are provided. In the system and method, a scene tag is selected for a portion 804 of a radiometric image data (800) of a location and a portion of the spatial data (200) associated with the first portion of the radiometric image data is selected. Based on the scene tag, a color space function (500, 600) for the portion of the spatial data is selected, where the color space function defines hue, saturation, and intensity (HSI) values as a function of an altitude coordinate of the spatial data. The portion of the spatial data is displayed using the HSI values selected from the color space function based on the portion of the spatial data. In the system and method, scene tags are each associated different classifications, where each color space function represents a different pre-defined variation in the HSI values for an associated classification.

Claims

1. A method for improving visualization and interpretation of spatial data of a location, comprising:

selecting a first scene tag from a plurality of scene tags for a first portion of a radiometric image data of said location;

selecting a first portion of said spatial data, said spatial data comprising a plurality of three-dimensional (3D) data points associated with said first portion of said radiometric image data;

selecting a first color space function for said first portion of said spatial data from a plurality of color space functions, said selecting based on said first scene tag, and each of said plurality of color space functions defining hue, saturation, and intensity (HSI) values as a function of an altitude coordinate of said plurality of 3D data points; and

displaying said first portion of said spatial data using said HSI values selected from said first color space function using said plurality of 3D data points associated with said first portion of said spatial data,

wherein said plurality of scene tags are associated with a plurality of classifications, and wherein each of said plurality of color space functions represents a different pre-defined variation in said HSI values associated one of said plurality of classifications.

2. The method of claim 1, wherein said selecting said first scene tag further comprises:

dividing said radiometric image data into a plurality of portions; and

selecting one of said plurality of scene tags for each of said plurality of portions.

3. The method of claim 1, wherein said selecting said first scene tag further comprises:

recognizing one or more types of features in said first portion of said radiometric image data; and

determining said first scene tag for said first portion of said spatial data based at least one of said types of features recognized in said first portion of said radiometric image data.

4. The method of claim 3, wherein said recognizing further comprises identifying said types of features based on performing at least one of a geometric analysis of said first portion of said radiometric image data and a spectral analysis of said first portion of said radiometric image data.

5. The method of claim 4, wherein said performing said geometric analysis comprises detecting at least one among edge features, corner features, blob features, or ridge features.

6. The method of claim 4, wherein said radiometric image data comprises image data for a plurality of spectral bands, and wherein said performing said spectral analysis comprises detecting features by evaluating at least one of said plurality of spectral bands.

7. The method of claim 6, wherein said evaluating said difference comprises computing a normalized vegetation value index (NVDI) values for each pixel in said radiometric image data, and wherein said recognizing further comprises identifying vegetation features based on said NVDI values.

8. A system for improving visualization and interpretation of spatial data of a location, comprising:

a storage element for receiving said spatial data and radiometric image data associated with said location; and

a processing element communicatively coupled to said storage element, wherein the processing element is configured for;

selecting a first scene tag from a plurality of scene tags for a first portion of a radiometric image data of said location;

selecting a first portion of said spatial data, said first portion of said spatial data comprising a plurality of three-dimensional (3D) data points associated with said first portion of said radiometric image data;

selecting a first color space function for said first portion of said spatial data from a plurality of color space functions, said selecting based on said first scene tag, and each of said plurality of color space functions defining hue, saturation, and intensity (HSI) values as a function of an altitude coordinate of said plurality of 3D data points; and

displaying said first portion of said spatial data using said HSI values selected from said first color space function using said plurality of 3D data points associated with said first portion of said spatial data,

wherein said plurality of scene tags are associated with a plurality of classifications, and wherein each of said plurality of color space functions represents a different pre-defined variation in said HSI values associated one of said plurality of classifications.

9. The system of claim 8, wherein said processing element is further configured during said selecting of said first scene tag for:

dividing said radiometric image data into a plurality of portions; and

selecting one of said plurality of scene tags for each of said plurality of portions.

10. The system of claim 8, wherein said processing element is further configured during said selecting of said first scene tag for:

recognizing one or more types of features in said first portion of said radiometric image data; and

determining said first scene tag for said first portion of said spatial data based at least one of said types of features recognized in said first portion of said radiometric image data.

11. The system of claim 10, wherein said processing element is further configured during said recognizing for:

identifying said types of features based on performing at least one of a geometric analysis of said first portion of said radiometric image data and a spectral analysis of said first portion of said radiometric image data.

12. The system of claim 11, wherein said performing said geometric analysis comprises detecting at least one among edge features, corner features, blob features, or ridge features.

13. The system of claim 11, wherein said radiometric image data comprises image data for a plurality of spectral bands, and wherein said performing said spectral analysis comprises detecting features by evaluating at least one of said plurality of spectral bands.

14. The system of claim 13, wherein said processing element is further configured during said evaluating said difference for computing a normalized vegetation value index (NVDI) values for each pixel in said radiometric image data, and wherein said processing element is further configured during said recognizing for identifying vegetation features based on said NVDI values.

15. A computer-readable medium, having stored thereon a computer program for improving visualization and interpretation of spatial data of a location, the computer program comprising a plurality of code sections, the plurality of code sections executable by a computer for causing the computer to perform the steps of:

selecting a first scene tag from a plurality of scene tags for a first portion of a radiometric image data of said location;

selecting a first portion of said spatial data, said spatial data comprising a plurality of three-dimensional (3D) data points associated with said first portion of said radiometric image data;

selecting a first color space function for said first portion of said spatial data from a plurality of color space functions, said selecting based on said first scene tag, and each of said plurality of color space functions defining hue, saturation, and intensity (HSI) values as a function of an altitude coordinate of said plurality of 3D data points; and

displaying said first portion of said spatial data using said HSI values selected from said first color space function using said plurality of 3D data points associated with said first portion of said spatial data,

wherein said plurality of scene tags are associated with a plurality of classifications, and wherein each of said plurality of color space functions represents a different pre-defined variation in said HSI values associated one of said plurality of classifications.

16. The computer-readable medium of claim 15, wherein said selecting said first scene tag further comprises code sections for:

dividing said radiometric image data into a plurality of portions; and

selecting one of said plurality of scene tags for each of said plurality of portions.

17. The computer-readable medium of claim 15, wherein said selecting said first scene tag further comprises code sections for:

recognizing one or more types of features in said first portion of said radiometric image data; and

determining said first scene tag for said first portion of said spatial data based at least one of said types of features recognized in said first portion of said radiometric image data.

18. The computer-readable medium of claim 17, wherein said recognizing further comprises code sections for:

identifying said types of features based on performing at least one of a geometric analysis of said first portion of said radiometric image data and a spectral analysis of said first portion of said radiometric image data.

19. The computer-readable medium of claim 18, wherein said performing said geometric analysis comprises code sections for detecting at least one among edge features, corner features, blob features, or ridge features.

20. The computer-readable medium of claim 19, wherein said radiometric image data comprises image data for a plurality of spectral bands, and wherein said performing said spectral analysis comprises code sections for computing a normalized vegetation value index (NVDI) values for each pixel in said radiometric image data, and wherein said recognizing further comprises code sections for identifying vegetation features based on said NVDI values.