The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing 2008 
2.4.1 Applicability for PolSAR Data: Here, the algorithm 
is applicable for PolSAR data segmentation and classification. 
The edge-detection-based segmentation algorithms are seldom 
used for PolSAR data, while PolSAR data can provide more 
information than traditional SAR data. It is considered that the 
parameters, H and alpha, derived from the target decomposition 
of the PolSAR data, have better discrimination for objects []. So 
the information of those two channels is more credible for 
feature extraction than that of other channels, e.g. VV, HH, HV 
etc. The experiment results in this paper give supports for this 
point. 
2.4.2 Edge Enhancement Template: Here 3X7 and 7X3 
windows are proposed as edge enhancing templates to enhance 
horizontal and vertical edge information. 
2.4.3 Canny Edge Detector: Canny edge detector is 
performed after a series of pre-processing procedures, such as 
edge enhancement. 
2.4.4 Region Merging: Large regions won’t be merged into 
others in the following region merging steps while small ones 
can be merged into any other one. 
Large regions won’t merge with each other in order to avoid 
the combination of heterogeneous regions across the undetected 
edges which really exist., In condition that two large regions are 
not merged into each other even though they satisfy the 
criterion for merging, this won’t effect the following processing, 
such as classification, enhancement and so on . As we know, 
the large regions contain enough pixels to represent the 
statistical characteristic of the region, which can avoid the 
influence of the speckles. 
Small regions can merge with each other or into large ones, 
where two cases are considered. If the pixel numbers in the 
small region is less than a threshold, it will be directly merged 
into the nearest region. Otherwise, the similarity between this 
region with the nearest one is considered, one threshold is set to 
decide whether it involves into merging. The minimum size is 
set to be 3 X 3 to ensure the segmentation accuracy of boundary 
regions. 
2.4.5 Point-to-region merge: Point-to-region merging is to 
realize the segmentation of the whole image. Some regions 
smaller than 3X3 and boundary pixels are left after region 
merging, which are called discrete points. In order to realize the 
thorough segmentation of the whole image, those discrete 
points should be merged into corresponding regions. In this step, 
Wishart distance of point-to-region or point-to-class is used as 
the criterion for merging or discrimination. 
3. EXPERIMENTS AND RESULTS 
Experiment Data Introduction 
as state farms. Figure 1 shows intensity image of VV 
polarization synthesization of the region, Flevoland. 
Figure 1. Intensity image of VV of the region, Flevoland 
Experiments 
Segmentation of the experiment data is performed using the 
algorithm proposed in this paper. Figure 2 shows the 
segmentation result, in which each region is given the mean 
value of H. In order to verify the validity of the segmentation 
result, a simple classification using the segment results [X] is 
performed and the result is compared with that got using point 
based classification method. The results are shown in Figure 3 
and Figure 4. 
From the analysis of results we can conclude four points bellow: 
First: There are no discrete points and seldom small regions in 
the segmentation results. 
Second: Boundaries are very clear, which can be seen from the 
segmentation results. 
Third: The algorithm, at the step of edge detection, has high 
efficiency and the time complexity is lower than that of RGW.