Object Based Image Analysis Tools for Opticks

Mohit Kumar, KS Rajan, Dustan Adkins

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OSGEO-India: FOSS4G 2012- First National Conference "Open Source Geospatial Resources to Spearhead Development and Growth” 25-27th October 2012, @ IIIT Hyderabad

Why object-based?

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• Opticks is an open source, remote sensing application that supports imagery, video (motion imagery), Synthetic Aperture Radar (SAR), multi-spectral, hyper-spectral, and other types of remote sensing data.

• Opticks can also be used as a remote sensing software development framework. Developers can extend Opticks functionality using its plug-in architecture and public application programming interface

• http://opticks.org

• Object based approach is better than conventional per-pixel analysis as it deals with considerably reduced number of units. This approach is not that much sensitive to noise and hence is spatially consistent.

OPTICKS ?

Workflow

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Input image(RGB)

Input image (CIELAB colour

space)

5 Dimensional feature space

Modes(local maximas) Clustering

Objects formed (backtracking the

modes)

Points in feature space collapsing

to one mode form an object.

Pruning (spatial Bandwidth)

Pruning (Spectral Bandwidth)

Pruning ( Minimum region area)

Image Segmentation (Meanshift)

Object attribution• Calculating textural, geometric and spectral features for the objects

made in the Segmentation step in a feature vector. • Area, Perimeter, Roundness, Compactness, Centroid, Contrast,

Coarseness, Direction, Roughness, Mean red, Mean green, Mean blue, std. deviation Red, std. deviation Green, std. deviation Blue.

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Segmented Image For every object in the image

Initialize a vector having all 16 features

Calculate value for every feature and save in the vector.

Classification• Mahalanobis Distance• Di,j

2 = (x-µj)`S-1(x-µj)• The class which has the least Mahalanobis

distance to the object i is the class of that object.

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Vectorization• Creates vector polygons for all connected regions of pixels in the

object image sharing a common pixel value.• Polygon features are created on the output layer, with polygon

geometries representing the polygons.• The class which has the least Mahalanobis distance to the object i is

the class of that object.

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The Input Orbview3 (4m) data of a part of delhi (500X500) The output of the objects with area less than 100.

Output of object having area 100-200 and classified as building. The shapefile(.shp) displaying the objects

Image Size Number of objects

Running time (sec)

512 X 512 153 3.1

1024 X 1024 435 24.55

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Image Size Number of objects Running time (sec)

256 X 256 49 0.249

512 X 512 193 1.133

1024 X1024 752 5.359

2048 X 2048 2965 31.60

4096 X 4096 11922 286.59

Performance AnalysisPerformance Analysis

Table 1 : Image segmentation

Table 2 : Object Attribution

Source Code

• https://github.com/mohitkharb/Opticks_GSOC2012

• http://opticks.org/confluence/display/~mohitkharb/Workflow+of+the+pluggin

• http://code.google.com/soc/

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Any Questions?

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