Object-based image analysis

OTB allows to implement Object-Based Image Analysis (OBIA) by using ITK's Label Object framework [1]. This allows to represent a segmented image as a set of regions and not anymore as a set of pixels. Added to the compression rate achieved by this kind of description, the main advantage of this approach is the possibility to operate at the segment (or object level).

A classical OBIA pipeline will use the following steps:

1. Image segmentation (the whole or only parts of it)
2. Image to LabelObjectMap (a kind of std::map<LabelObject>) transformation
3. Eventual relabeling
4. Attribute computation for the regions using the image before segmentation
   1. Shape attributes (available in the original IJ submission)
   2. Statistics attributes (available in the original IJ submission)
   3. Attributes for radiometry, textures, etc. (to be added in OTB)
5. Object filtering
   1. Remove/select objects under a condition (area less than X, NDVI higher than X, etc.)
   2. Keep N objects
6. LabelObjectMap to image transformation

There are some missing things which would be very useful in OTB

1. LabelObject to VectorData conversions
2. Object-based classification