Quality Report Generated with Pro version

Transcription

1 Quality Report Generated with Pro version Important: Click on the different icons for: Help to analyze the results in the Quality Report Additional information about the sections Click here for additional tips to analyze the Quality Report Summary Project Processed Average Ground Sampling Distance (GSD) poem_etagnieres_200ha :10: cm / 4.77 in Area Covered km2 / ha / sq. mi. / acres 05h:30m:15s Time for Initial Processing (without report) Quality Check Images median of keypoints per image Dataset 5252 out of 5260 images calibrated (99%), all images enabled, 2 blocks Camera Optimization 0.03% relative difference between initial and optimized internal camera parameters Matching median of matches per calibrated image Georeferencing yes, no 3D GCP Preview Figure 1: Orthomosaic and the corresponding sparse Digital Surface Model (DSM) before densification. Calibration Details

2 Calibration Details Number of Calibrated Images 5252 out of 5260 Number of Geolocated Images 5260 out of 5260 Initial Image Positions Figure 2: Top view of the initial image position. The green line follows the position of the images in time starting from the large blue dot. Computed Image/GCPs/Manual Tie Points Positions Figure 3: Offset between initial (blue dots) and computed (green dots) image positions as well as the offset between the GCPs initial positions (blue crosses) and their computed positions (green crosses) in the top-view (XY plane), front-view (XZ plane), and side-view (YZ plane). Red dots indicate disabled or uncalibrated images.

3 Overlap Number of overlapping images: Figure 4: Number of overlapping images computed for each pixel of the orthomosaic. Red and yellow areas indicate low overlap for which poor results may be generated. Green areas indicate an overlap of over 5 images for every pixel. Good quality results will be generated as long as the number of keypoint matches is also sufficient for these areas (see Figure 5 for keypoint matches). Bundle Block Adjustment Details Number of 2D Keypoint Observations for Bundle Block Adjustment Number of 3D Points for Bundle Block Adjustment Mean Reprojection Error [pixels] Internal Camera Parameters Sequoia_4.0_1280x960 (Green). Sensor Dimensions: [mm] x [mm] EXIF ID: Sequoia_4.0_1280x960 Initial Optimized Poly[0] Poly[1] Poly[2] Poly[3] Poly[4] c d e f Point x Point y The number of Automatic Tie Points (ATPs) per pixel averaged over all images of the camera model is color coded between black and white. White indicates that, in average, more than 16 ATPs are extracted at this pixel location. Black indicates that, in average, 0 ATP has been extracted at this pixel location. Click on the image to the see the average direction and magnitude of the reprojection error for each pixel. Note that the vectors are scaled for better visualization. Internal Camera Parameters Sequoia_4.0_1280x960 (Red). Sensor Dimensions: [mm] x [mm] EXIF ID: Sequoia_4.0_1280x960

4 Initial Optimized Poly[0] Poly[1] Poly[2] Poly[3] Poly[4] c d e f Point x Point y The number of Automatic Tie Points (ATPs) per pixel averaged over all images of the camera model is color coded between black and white. White indicates that, in average, more than 16 ATPs are extracted at this pixel location. Black indicates that, in average, 0 ATP has been extracted at this pixel location. Click on the image to the see the average direction and magnitude of the reprojection error for each pixel. Note that the vectors are scaled for better visualization. Internal Camera Parameters Sequoia_4.0_1280x960 (Red edge). Sensor Dimensions: [mm] x [mm] EXIF ID: Sequoia_4.0_1280x960 Initial Optimized Poly[0] Poly[1] Poly[2] Poly[3] Poly[4] c d e f Point x Point y The number of Automatic Tie Points (ATPs) per pixel averaged over all images of the camera model is color coded between black and white. White indicates that, in average, more than 16 ATPs are extracted at this pixel location. Black indicates that, in average, 0 ATP has been extracted at this pixel location. Click on the image to the see the average direction and magnitude of the reprojection error for each pixel. Note that the vectors are scaled for better visualization. Internal Camera Parameters Sequoia_4.0_1280x960 (NIR). Sensor Dimensions: [mm] x [mm] EXIF ID: Sequoia_4.0_1280x960 Initial Optimized Poly[0] Poly[1] Poly[2] Poly[3] Poly[4] c d e f Point x Point y The number of Automatic Tie Points (ATPs) per pixel averaged over all images of the camera model is color coded between black and white. White indicates that, in average, more than 16 ATPs are extracted at this pixel location. Black indicates that, in average, 0 ATP has been extracted at this pixel location. Click on the image to the see the average direction and magnitude of the reprojection error for each pixel. Note that the vectors are scaled for better visualization. Camera Rig «Sequoia» Relatives. Images: 5260 Transl X [m] Transl Y [m] Transl Z [m] Rot X [degree] Rot Y [degree] Rot Z [degree] Sequoia_4.0_1280x960 (Red) Reference Camera Sequoia_4.0_1280x960 (Green) Initial Optimized values

5 Sequoia_4.0_1280x960 (Red edge) Initial Optimized values Sequoia_4.0_1280x960 (NIR) Initial Optimized values Note: The reference camera of the rig has changed to Sequoia_4.0_1280x960 (Red) in order to attain better results in the calibration. 2D Keypoints Table Median Min Max Mean D Keypoints Table for Camera Sequoia_4.0_1280x960 (Green) Median Min Max Mean D Keypoints Table for Camera Sequoia_4.0_1280x960 (Red) Median Min Max Mean D Keypoints Table for Camera Sequoia_4.0_1280x960 (Red edge) Median Min Max Mean D Keypoints Table for Camera Sequoia_4.0_1280x960 (NIR) Median Min Max Mean Median / 75% / Maximal Number of Matches Between Camera Models Sequoia_4.0_1... (Green) Sequoia_4.0_ (Red) Sequoia_4...(Red edge) Sequoia_4.0_1280x960 (Green) 22 / 93 / / 92 / / 26 / / 23 / 975 Sequoia_4.0_1280x960 (Red) 71 / 342 / / 31 / / 31 / 874 Sequoia_4.0_1280x960 (Red edge) Sequoia_4.0_128...(NIR) 17 / 93 / / 51 / 2216 Sequoia_4.0_1280x960 (NIR) 23 / 135 / 3460

6 3D Points from 2D Keypoint Matches Number of 3D Points Observed In 2 Images In 3 Images In 4 Images In 5 Images In 6 Images In 7 Images In 8 Images In 9 Images In 10 Images In 11 Images In 12 Images 9727 In 13 Images 7221 In 14 Images 5751 In 15 Images 4557 In 16 Images 3499 In 17 Images 2848 In 18 Images 2306 In 19 Images 1873 In 20 Images 1508 In 21 Images 1254 In 22 Images 1108 In 23 Images 855 In 24 Images 741 In 25 Images 622 In 26 Images 499 In 27 Images 406 In 28 Images 358 In 29 Images 297 In 30 Images 269 In 31 Images 199 In 32 Images 185 In 33 Images 171 In 34 Images 144 In 35 Images 130 In 36 Images 105 In 37 Images 99 In 38 Images 93 In 39 Images 73 In 40 Images 63 In 41 Images 58 In 42 Images 47 In 43 Images 45 In 44 Images 31 In 45 Images 41 In 46 Images 28 In 47 Images 20 In 48 Images 22 In 49 Images 12 In 50 Images 18 In 51 Images 6 In 52 Images 7 In 53 Images 11 In 54 Images 6 In 55 Images 5 In 56 Images 6 In 57 Images 3

7 In 58 Images 2 In 59 Images 3 In 62 Images 1 In 63 Images 2 In 65 Images 2 In 66 Images 2 2D Keypoint Matches Number of matches Figure 5: Top view of the image computed positions with a link between matching images. The darkness of the links indicates the number of matched 2D keypoints between the images. Bright links indicate weak links and require manual tie points or more images. Geolocation Details Absolute Geolocation Variance 0 out of 5252 geolocated and calibrated images have been labeled as inaccurate. Min Error [m] Max Error [m] Geolocation Error X [%] Geolocation Error Y [%] Geolocation Error Z [%] Mean [m] Sigma [m] RMS Error [m] Min Error and Max Error represent geolocation error intervalsbetween -1.5 and 1.5 times the maximum accuracy of all the images. Columns X, Y, Z show the percentage of images with geolocation errors within the predefined error intervals. The geolocation error is the difference between the intial and computed image positions. Note that the image geolocation errors do not correspond to the accuracy of the observed 3D points. Relative Geolocation Variance

8 Relative Geolocation Variance Relative Geolocation Error Images X [%] Images Y [%] Images Z [%] [-1.00, 1.00] [-2.00, 2.00] [-3.00, 3.00] Mean of Geolocation Accuracy [m] Sigma of Geolocation Accuracy [m] Images X, Y, Z represent the percentage of images with a relative geolocation error in X, Y, Z. Geolocation Orientational Variance RMS [degree] Omega Phi Kappa Processing Options Geolocation RMS error of the orientation angles given by the difference between the initial and computed image orientation angles. Hardware Operating System Camera Model Name Camera Model Name Camera Model Name Camera Model Name Image Coordinate System Output Coordinate System Detected template: CPU: Intel(R) Core(TM) i GHz RAM: 32GB GPU: NVIDIA GeForce GTX 760 (Driver: ) Windows 8.1 Pro with Media Center, 64-bit Sequoia_4.0_1280x960 (Green) Sequoia_4.0_1280x960 (Red) Sequoia_4.0_1280x960 (Red edge) Sequoia_4.0_1280x960 (NIR) WGS84 (egm96) WGS84 / UTM zone 32N (egm96) No template available Keypoints Image Scale Full, Image Scale: 2 Advanced: Matching Image Pairs Advanced: Matching Strategy Advanced: Keypoint Extraction Advanced: Calibration Rig «Sequoia» processing Aerial Grid or Corridor Use Geometrically Verified Matching: yes Targeted Number of Keypoints: Custom, Number of Keypoints: Calibration Method: Alternative, Internal Parameters Optimization: All, External Parameters Optimization: All, Rematch: Custom yes optimize relative rotation Point Cloud Densification details Processing Options Image Scale multiscale, 1/2 (Half image size, Default) Point Density Low (Fast) Minimum Number of Matches 3 3D Textured Mesh Generation no Advanced: Matching Window Size 7x7 pixels Advanced: Image Groups NIR, Red edge, Red, Green Advanced: Use Processing Area yes Advanced: Use Annotations yes Advanced: Limit Camera Depth Automatically no Time for Point Cloud Densification 01h:31m:57s Time for 3D Textured Mesh Generation NA

9 Results Number of Processed Clusters 4 Number of Generated Tiles 4 Number of 3D Densified Points Average Density (per m 3 ) 0.59 DSM, Orthomosaic and Index Details Processing Options DSM and Orthomosaic Resolution 1 x GSD (12.1 [cm/pixel]) DSM Filters Noise Filtering: yes, Surface Smoothing: yes, Sharp Index Calculator: Radiometric Calibration yes Index Calculator: Reflectance Map yes, Resolution [cm/pixel]: -1, Merge Tiles: no Index Calculator: Indices ndvi Index Calculator: Index Polygon Shapefile [cm/grid]: 400 Time for Orthomosaic Generation 03h:41m:45s Time for Reflectance Map Generation 03h:10m:31s Time for Index Map Generation 06m:38s