Geospatial raster data is a heavily used product in Geographic Information Systems and
Photogrammetry. Raster data typically can represent imagery and Digital Elevation Models (DEM). The
-standard library for loading GIS imagery is the Geographic Data Abstraction Library (GDAL). In this
+standard library for loading GIS imagery is the Geographic Data Abstraction Library [(GDAL)](http://www.gdal.org). In this
example, we will show techniques for loading GIS raster formats using native OpenCV functions. In
addition, we will show some an example of how OpenCV can use this data for novel and interesting
purposes.
The primary objectives for this tutorial:
-- How to use OpenCV imread to load satellite imagery.
-- How to use OpenCV imread to load SRTM Digital Elevation Models
+- How to use OpenCV [imread](@ref imread) to load satellite imagery.
+- How to use OpenCV [imread](@ref imread) to load SRTM Digital Elevation Models
- Given the corner coordinates of both the image and DEM, correllate the elevation data to the
image to find elevations for each pixel.
- Show a basic, easy-to-implement example of a terrain heat map.
Notes
-----
-### Lat/Lon (Geodetic) Coordinates should normally be avoided
+### Lat/Lon (Geographic) Coordinates should normally be avoided
-The Geodetic Coordinate System is a spherical coordinate system, meaning that using them with
+The Geographic Coordinate System is a spherical coordinate system, meaning that using them with
Cartesian mathematics is technically incorrect. This demo uses them to increase the readability and
is accurate enough to make the point. A better coordinate system would be Universal Transverse
Mercator.
the SRTM file located at the USGS here.
[<http://dds.cr.usgs.gov/srtm/version2_1/SRTM1/Region_04/N37W123.hgt.zip>](http://dds.cr.usgs.gov/srtm/version2_1/SRTM1/Region_04/N37W123.hgt.zip)
-
+
-
+
-
+
-/**
+/*
* gdal_image.cpp -- Load GIS data into OpenCV Containers using the Geospatial Data Abstraction Library
*/
-/// OpenCV Headers
+// OpenCV Headers
#include "opencv2/core/core.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
-/// C++ Standard Libraries
+// C++ Standard Libraries
#include <cmath>
#include <iostream>
#include <stdexcept>
using namespace std;
-/// define the corner points
-/// Note that GDAL can natively determine this
+// define the corner points
+// Note that GDAL library can natively determine this
cv::Point2d tl( -122.441017, 37.815664 );
cv::Point2d tr( -122.370919, 37.815311 );
cv::Point2d bl( -122.441533, 37.747167 );
cv::Point2d br( -122.3715, 37.746814 );
-/// determine dem corners
+// determine dem corners
cv::Point2d dem_bl( -122.0, 38);
cv::Point2d dem_tr( -123.0, 37);
-/// range of the heat map colors
+// range of the heat map colors
std::vector<std::pair<cv::Vec3b,double> > color_range;
-/// List of all function prototypes
+// List of all function prototypes
cv::Point2d lerp( const cv::Point2d&, const cv::Point2d&, const double& );
cv::Vec3b get_dem_color( const double& );
-/**
+/*
* Linear Interpolation
* p1 - Point 1
* p2 - Point 2
((1-t)*p1.y) + (t*p2.y));
}
-/**
+/*
* Interpolate Colors
*/
template <typename DATATYPE, int N>
return output;
}
-/**
+/*
* Compute the dem color
*/
cv::Vec3b get_dem_color( const double& elevation ){
return lerp( color_range[idx].first, color_range[idx+1].first, t);
}
-/**
+/*
* Given a pixel coordinate and the size of the input image, compute the pixel location
* on the DEM image.
*/
return output;
}
-/**
+/*
* Convert a pixel coordinate to world coordinates
*/
cv::Point2d pixel2world( const int& x, const int& y, const cv::Size& size ){
return lerp( leftSide, rightSide, rx );
}
-/**
+/*
* Add color to a specific pixel color value
*/
void add_color( cv::Vec3b& pix, const uchar& b, const uchar& g, const uchar& r ){
}
-/**
+/*
* Main Function
*/
int main( int argc, char* argv[] ){
- /**
+ /*
* Check input arguments
*/
if( argc < 3 ){
return 1;
}
- /// load the image (note that we don't have the projection information. You will
- /// need to load that yourself or use the full GDAL driver. The values are pre-defined
- /// at the top of this file
+ // load the image (note that we don't have the projection information. You will
+ // need to load that yourself or use the full GDAL driver. The values are pre-defined
+ // at the top of this file
cv::Mat image = cv::imread(argv[1], cv::IMREAD_LOAD_GDAL | cv::IMREAD_COLOR );
- /// load the dem model
+ // load the dem model
cv::Mat dem = cv::imread(argv[2], cv::IMREAD_LOAD_GDAL | cv::IMREAD_ANYDEPTH );
- /// create our output products
+ // create our output products
cv::Mat output_dem( image.size(), CV_8UC3 );
cv::Mat output_dem_flood( image.size(), CV_8UC3 );
- /// for sanity sake, make sure GDAL Loads it as a signed short
+ // for sanity sake, make sure GDAL Loads it as a signed short
if( dem.type() != CV_16SC1 ){ throw std::runtime_error("DEM image type must be CV_16SC1"); }
- /// define the color range to create our output DEM heat map
+ // define the color range to create our output DEM heat map
// Pair format ( Color, elevation ); Push from low to high
// Note: This would be perfect for a configuration file, but is here for a working demo.
color_range.push_back( std::pair<cv::Vec3b,double>(cv::Vec3b( 188, 154, 46), -1));
projects / platform / upstream / opencv.git / commitdiff