New answers tagged erdas-imagine
Histogram matching works by forcing the histogram of one image to match as closely as possible the histogram of a second target image. I'm afraid that it won't work on a single image. (There is the exception of using Histogram Matching to force an image to theoretical distribution, like the Gaussian, but that won't help in this case either.) Also, I'm not ...
You could try Linear Contrast Stretch (Linear Contrast Stretch, Pg 145) in ERDAS IMAGINE. This tool will assess the minimum and maximum DN/pixel value in your image and stretch it in the range of 0-255. The same can also be done using ArcGIS, as you required. Linear Stretch using ArcGIS. This is a form of radiometric enhancement of the image, wherein you ...
You will want to stretch your floating point data from (-1 to 1) to (0 - 255). You can accomplish this very easily in Erdas Imagine: Raster tab > Resolution Group > Radiometric > Rescale
Using ArcGis Raster Calculator multiply by 127 and then add 128. This will give you a value between 0 and 255 which will be floating point then use Int to convert to an integer and Copy Raster specifying 8 bit unsigned as the output pixel_type. Another way to do this is to do a nice stretch in ArcMap and then right click on the layer, select data::export ...
Late answer, but better than nothing: ATCOR scales its output per default into the 8-bit range. If you need to have a 16-bit output you have to set the Factor for Reflectance (found in the Main Menu) to values ≥ 10 so it will be scaled into the 16-bit range. With fcref=100 (supported since ATCOR 2010.1) the output data ranges from 0 to 10,000 which will be ...
While loading the image itself, in the File window you should find another Tab that allows you to open the Image in Pseudo color form. Once done, you can view the histogram distribution and alter the color of the pixel values of your choice. Hope this helps !!!
Two possible solutions: try using a smaller cloud probability like 12.5 in Fmask try using the most recent Tmask algorithm that uses the multi-temporal information.
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