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Rescaling an NDVI or EVI from -1 to 1, to 0 to 1, uses the Rescale function (under Raster, Radiometric). Clipping the top and bottom 0.5% is a percentage linear contrast stretch. To do this in ERDAS 2013, click on Panchromatic, then General Contrast. This brings up the Contrast Adjust window (seen below), and you can choose a variety of different methods ...


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A good documentation can be found here (.pdf). Also look at the Erdas forum here. Another good resource is ERDAS IMAGINE 2014 Python Examples


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.bls files are relatively easy to create. It's the .bcf files that are very difficult to create in python because ERDAS has horrible batch creation and debugging. I've done both in Python before, and here is an excerpt from the .bls creation. It's from ERDAS 2011, though I think it still works with 2013..... md = <folder> images = arcpy.ListRasters() ...


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One of the most common reason for the covariance matrix that is not invertible from samples is the presence of null variance for one band (all your pixel in one band have the same value). In this case, increasing the size of the sample increase the chances to have a non null variance. Note that the band 6 (thermal) is the most likely to be constant, ...


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Apollo can handle various image formats including geotiff, rrd, img, etc. If you already have your images in tiff format it makes sense to simply use that.


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so i guess this is a classified image? i can think of two more ideas : 1. i think for each class you can (start from biggest to lowest class) you can do morphological operations - open -> close (dilate -> erode). 2. treat them as polygons, find holes and remove them you can do this for example in matlab


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i dont know what version of erdas are you using, but in erdas 2011: go to raster - > radiometric -> rescale and choose your min/max values and it will stretch all values. i dont know about the 2 decimal format.



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