View source for Exercise 09: Segmentation algorithms

==Segmentation in Monteverdi==
# Open Monteverdi by double-clicking the icon on the Desktop 
# Select {{mitem|text=File --> Open dataset}} and browse for ''188_pcs_indices.tif''
# Open the panchromatic image saved in ''landsat8/DOY88/SUB_LC81950242013188LGN00_B8.tif'' via {{mitem|text=File --> Open dataset}}. 
# In order to equalize the spatial extent and resolution of the two maps, select {{mitem|text=Geometry --> Superimpose two images}} Select image ''188_pcs_indices.tif)'' for reprojection and  ''SUB_LC81950242013188LGN00_B8.tif'' as reference image. Confirm with {{button|text=OK}}. 
# To generate an image with the characteristics of the multispectral image with the panchromatic resolution, select {{mitem|text=Filtering --> Pansharpening --> Simple RCA Pansharpening}} Select image to reproject (''188_pcs_indices.tif'') and the reference image for reprojection (''SUB_LC81950242013188LGN00_B8.tif''). Confirm with {{button|text=OK}}.
# Save the processed image: Right-click the file of the output image (Pan SharpenedImageOutput) and select {{mitem|text=Export dataset --> pansharpened188.tif (32 bit)}}. Confirm with {{button|text=OK}}.
# Load the generated image (''pansharpened188.tif'') into the [[QGIS]] project and compare it to the original multispectral image (''188_pcs_indices.tif'').
# As segmentation is a procedure that requires high computational capacity, it is recommended o select a subset of the sharpened images: Select {{mitem|text=File --> Extract ROI from dataset}} and select the image ''pansharpened188.tif'' as input. Draw a box in the {{button|text=select ROI}} window and confirm with {{button|text=OK}} (figure '''F'''). 
# Applying the segmentation algorithm:
# Open {{button|text=Filtering --> Mean shift clustering}} and select the ROI extracted from ''pansharpened188.tif''. Once you see the {{button|text=Mean shift module}} window you can change the parameters spectral value, spatial radius and opacity to find the pool of values that fit best to the characteristics of the image (e.g. figure '''G''').
# When the set of values that best fit to the image are found, the segmentation parameters can be applied to the whole image via {{button|text=Processing}}: Select {{mitem|text=Processing  --> Orfeo Toolbox --> Segmentation --> Mean Shift segmentation (large scale, vector output)}}. Use ''pansharpened188.tif'' as input map with the parameters selected in {{button|text=Mean Shift module}} from Monteverdi software.