Image processing: Difference between revisions

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* simple "cosine correction" using {{cmd|r.sunmask}}, {{cmd|r.mapcalc}} (tends to overshoot when slopes are high)
* simple "cosine correction" using {{cmd|r.sunmask}}, {{cmd|r.mapcalc}} (tends to overshoot when slopes are high)
* Minnaert or other corrections with i.topo.corr (from [[GRASS AddOns]])
* In {{AddonCmd|i.topo.corr}} (from GRASS AddOns) the following correction methods are implemented: cosine, minnaert, percent, c-factor.


=== Cloud removal ===
=== Cloud removal ===

Revision as of 14:33, 24 September 2010

Introduction

Satellite imagery and orthophotos (aerial photographs) are handled in GRASS as raster maps and specialized tasks are performed using the imagery (i.*) modules. All general operations are handled by the raster modules.

  • Data import is generally handled by the r.in.gdal module


Screenshots

Importing

Satellite Data

Ocean Color

Sea Surface Temperature (SST)

High resolution data

Orthophotos

Preprocessing

See Satellite Overpass Predictor

Geometric preprocessing/Georectification

  • Tcl/Tk georectification tool is available from the File menu in the GUI.
  • i.points, i.vpoints (scanned maps, satellite images)
  • i.ortho.photo (aerial images)

A multi-band image may be grouped and georectified with a single set of ground control points (i.group, i.target, i.rectify).

See also the Georeferencing wiki page

Radiometric preprocessing

Correction for atmospheric effects

Correction for topographic/terrain effects

In rugged terrain, such correction might be useful to minimize negative effects.

  • simple "cosine correction" using r.sunmask, r.mapcalc (tends to overshoot when slopes are high)
  • In i.topo.corr (from GRASS AddOns) the following correction methods are implemented: cosine, minnaert, percent, c-factor.

Cloud removal

Image classification

See: Image classification page

Filtering

Enhancements

Radiometric Enhancements

Geometric Enhancements

Optimal channel selection for color composites

Stereo anaglyphs

Ideas collection for improving GRASS' Image processing capabilities

Below modules need some tuning before being added to GRASS 6. Volunteers welcome.

Spectral unmixing

Spectral angle mapping

Geocoding

Image matching

  • i.points.auto: automated search of GCPs based on FFT correlation (as improved i.points)
Reference: M. Neteler, D. Grasso, I. Michelazzi, L. Miori, S. Merler, and C. Furlanello, 2005: An integrated toolbox for image registration, fusion and classification. International Journal of Geoinformatics, 1(1), pp. 51-61 PDF

Image classification

Stereo

This is stand-alone stereo modeling software (DEM extraction etc). Waits for integration into GRASS.

Lidar LAS format

LAS Tools by M. Isenburg, Howard Butler et al.: http://www.liblas.org

   las2txt | r.in.xyz in=- fs=" "

(see LIDAR)

Improving the existing code

It might be sensible to merge the various image libraries:

  • GRASS 6 standard libs:
    • lib/imagery/: standard lib, in use (i.* except for i.points3, i.rectify3, see below)
    • imagery/i.ortho.photo/libes/: standard lib, in use (i.ortho.photo, photo.*)
  • GRASS 5 (! only) image3 lib:
    • libes/image3/: never finished improvement which integrated the standard lib and the ortho lib. Seems to provide also ortho rectification for satellite data (i.points3, i.rectify3)
  • GRASS 5/6 image proc commands:
    • merge of i.points, i.vpoints, i.points3 (see above)
    • merge of i.rectify and i.rectify3 (see above)
    • addition of new resampling algorithms such as bilinear, cubic convolution (take from r.proj or r.resamp.aggreg)
    • add other warping methods (maybe thin splines from GDAL?): Addons#i.warp
    • implement/finish linewise ortho-rectification of satellite data

Bibliography