Brief Introduction
This software has realized the following methods for segmentation:
Graph based segmentation [2] (GS);
Quad tree segmentation [1] (QT) (similar to that implemented in eCognition [6] and that as a
step in HSMR [7], but in a bottom-up fashion);
Hierarchical Clustering segmentation (HC) (i.e., Multiresolution segmentation [3], but with
multiple homogeneity criterion, basic data structures detailed in [5]);
The two-stage methods, GS-HC, QT-HC (described in [1] in detail)
Pyramid mean shift segmentation implemented in OpenCV 1.0
Mean shift segmentation [8] of Dorin Comaniciu (resembles EDISON [9])
Watershed segmentation [10] of Vincent and Soille
And for edge detection, SUSAN [11], Sobel, Canny edge detector are incorporated.
For classification,
MRF classification initialized by K-means by ICM, Gibbs sampler, Metropolis etc.
K-means clustering
For building hypotheses generation on panchromatic images,
Hierarchical region growing and then apply threshold to region properties (i.e., decision tree),
K-means clustering, connected region labeling and then decision tree,
For change detection,
Rosin’s automatic thresholding [12],
Gradient image correlation thresholding [13],
window intensity correlation thresholding [14],
Window histogram matching using OpenCV.
Multilevel parcel based change detection using K-means (resembles [15] but using k-means
to decide threshold)
How to install?
Requirement: OpenCV 1.0 has been installed on your computer and the system variable path has
been set. The GDAL library is used in this software to support for multiple image formats and
various vector formats, such as shp. And the needed source code for GDAL is already included in
the source code zip file.
(1) Download the source code. zip file from the CSDN (Search keywords image segmentor source
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