Aerial Image Processing Software and Workflows

Hi all,

I am starting this discussion to bring to together all of the different types of software people are using to process photos collected with their drones and also what they are using it for and what limitations they are finding.

I am currently using the following software:

Agisoft Photoscan Pro

-The data I am running through it was not collected for photogrammetry so I am having some difficulties

-Some images are collected in winter with on the ground making it harder for photoscan to find matching points

-Some images do not have enough overlap or not good enough quality

-Images over forested landscapes sometimes have problems finding matching points

Microsoft ICE

I have using this for quick stitching of images with too little overlap for Photoscan.

I have found it does not work well for long linear set of images

Google Earth

I use google earth to find coordinates for ground control points or georeferencing.

QGIS

Is an open source GIS software that I use for georeferencing stitched or single images and creating data from the images

I also do a lot of work with LiDAR data and as such am very interested in classifying the point cloud that I can create with Photoscan. The new version has a tool for classifying ground points and then allowing you manually sort the rest. But I am also interested in using the one thing the advantage that photogrammetrically derived points clouds have over raw Lidar data and that is point cloud colours. I am interested in creating a work flow to classify orthos created into feature types (as can already be done) and then assigning these feature type to the point cloud that is also created.

thanks,

jarrett

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  • Open source solutions, check out the AerialPhoto SE and Visual SFM (links on http://www.photogrammetric-vision.com/software.html). MicMac & Apero (http://www.micmac.ign.fr/) is also another interesting solution for complete workflow.

    We are using a lot of UAVs (http://www.photogrammetric-vision.com/uavs.html) for a long time and many applications (http://www.photogrammetric-vision.com/mapping-with-uav--rf.html  http://www.photogrammetric-vision.com/archeophoto.html http://www.photogrammetric-vision.com/hawkeye.html http://www.photogrammetric-vision.com/orthophotos-from-color-point-... http://www.photogrammetric-vision.com/plant-stress-analysis.html

    The main commercial s/w that we are using is PhotoScan from Agisoft, but you may also want to consider Pix4D and Photomod UAV module for ful photogrammetric processing. The latter ones are more expensive than the formar one. 

    More open/free solutions will appear sooner or later.

    • Concerning the pricing of Pix4D software, a new version of their product was released in January 2014: Pix4Dmapper. It is possible to rent it on a monthly / yearly basis or purchase a full license. 

      Read more about the pricing table: http://pix4d.com/buy_rent/

      Or request a free trial !

  • Hey Guys,

    Another interesting post I came across:

    http://arc-team-open-research.blogspot.ca/2013/12/from-drone-aerial...

    They used a python module called Python Photogrammetry Toolbox (http://www.arc-team.homelinux.com/arcteam/ppt.php) to create the orthophoto.

    Arnaud

  • Hello Jarrett,  

    You have used our previous software (Pix4uav) to process the dataset. Why not have a try with Pix4Dmapper that has new features such as:

    • Generates much more points
    • Supports oblique datasets (such as the one published)
    • Let's you easily assess the accuracy of the results using the rayCloud
    • Computes orthomosaics with less distortions

     

    And please share your results!

  • Agisoft Pro is certainly the best quality for the price, in addition to their constant updates free for two years. We have been working with Agisoft Pro for a year now and the results are expectaculares in resolution, precision and products generated, although we must not forget that the camera should be of good optical quality with a better final product quality. Also important is an overlap of more than 60% to 80% orthoimage and digital surface models.

  • So I used the "topography_cadastre_switzerland" dataset of a town that can be downloaded from the Pix4Uav website and I now have a ortho and a point cloud.3692928647?profile=original3692928844?profile=originalI am now going to try to classify the image using some of the tools I mentioned earlier and apply it to the point cloud.

    -jarrett

  • I really like Agisoft Photoscan Pro, it would just be nice to create a completey open source and free work flow for anyone to use for any purpose.

    Anyways here is a comparison of some results I got from Pix4UAV:

    3692928582?profile=originalAnd the same dataset run through Agisoft Photoscan:3692928725?profile=originalThey both took around the same amount of time to process (actually Photoscan may have been a bit faster). Visually the output from Photoscan is much cleaner, less noise, colours where they should be. Spatially they are both in the same spot. It just seems that Photoscan picked out finer details.

    Now the next step is to classify the point cloud data. I am think that classifying the orthophoto into polygons representing different features and then assigning these polygons to the point cloud is the way to go.

    Some of the different options I am looking at include:

    -http://orfeo-toolbox.org/otb/otbqgis.html

    -http://www.samplepoint.org/index.html

    -http://blogs.esri.com/esri/arcgis/2010/08/09/image-classification-t...

    -jarrett

  • Hi Jarrett,

    You can use as well the libraries MicMac developed by the French Cartographic Agency for stitching your images:

    http://logiciels.ign.fr/?Telechargement,20

    I've never used it yet, but I heard that the results are quite good.

    Installation - Setup - LOGICIELS
    Toutes les instructions d'installation à jour et les liens sont disponibles ici : All up-to-date installation instructions and links are available (.…
  • I've been using VisualSfM and CMPMVS. You can run these on Windows, but need 16G memory and an Nvidia card to process the results. With less than 16G memory you need to tweak the cmpmvs file to lower the point cloud data size.

    Disadvantages of CMPMVS is that it sometimes leaves holes and in certain cases produces vertices below the mesh surface. This makes normal recalculations trickier.

    On ICE... I did a demo on diydrones some time ago showing its results. I think it's pretty poor at performing the actual matching. I reckon it's probably more useful for pano shots without too much rotation or up to 3-4 photo panorama shots:

    http://diydrones.com/profiles/blogs/photo-stitching-with-visualsfm-...

    There are other tools like meshlab, rapidexplorer and cloudcompare to process the point cloud data. Those each have useful functions for density reduction, normal recalculation and so on. I did a demo some time ago on how you can use meshlab and other tools to utilize the areas in visualizations or games:

    http://diydrones.com/profiles/blogs/2d-images-to-3d-virtualized-lan...

    http://www.cs.jhu.edu/~misha/Code/PoissonRecon/Version5.5/

    I use commercial tools for professional work: pix4uav and menci. These produce far better results. You can't use vsfm or cmpmvs commercially without having an agreement with the original authors.

    Getting the data georeferenced is more tricky with visualSfM and CMPMVS. Basically you need to figure out where your cameras were. I updated the photo's EXIF (easiest) with each point to get them located correctly.

    • Dear Sir,

      I am using VisualSFM to process 27 images taken by a fixed wing UAV(for my final year thesis-Undergraduate study).I downloaded the data from Trimble UASMaster Sample datasets. The 3D point clouds have large gaps and holes in many places.Other software like LPS,Agisoft and PIX4D have generated satisfactory results.I have tried contacting different experts and data providers but i am not getting satisfactory response which can solve this issue. Please kindly suggest me how to deal with this problem.

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