Gareth, Frank implemented a method to merge a hillshade and color-mapped image in GDAL/python (called hsv_merge.py). This code could be changed to meet your needs. Otherwise you might be able to stretch the hillshade using the scale parameter in gdal_translate prior to using hsv_merge.py.
https://svn.osgeo.org/gdal/trunk/gdal/swig/python/samples/ example workflow: http://linfiniti.com/2010/12/a-workflow-for-creating-beautiful-relief-shaded-dems-using-gdal/ There many different methods to blend these two files together. If you write an update to hsv_merge.py it would be good to hear about. For a C++ (faster) implementation of hsv_merge, NASA Ames have released binaries (and code) within their Stereo Pipeline (ASP) package. http://ti.arc.nasa.gov/tech/asr/intelligent-robotics/ngt/stereo/ Good luck, Trent On Wed, Mar 18, 2015 at 8:41 AM, Gareth Grewcock <[email protected]> wrote: > Hi - firstly, apologies if the gdal-dev mailing is not the appropriate > mailing list, please advise a more suitable place to post if so. > > > > My objective is to create a hillshaded color-relief image of a DEM using > commandline/programmatic means only, so the process can be automated and > combined within an existing GMT/GDAL workflow. > > > > Currently, I can generate both hillshaded and color-relief rasters using > gdaldem and combine them with Mapnik (using opacity) to generate a my final > rendered image. However, this process will use the min-max values in the > grayscale hillshaded image. > > > > However, I can achieve an improved or sharper hillshaded image when I > manually use QGIS to further process the hillshaded image by: > > 1. Adding the hillshaded raster to QGIS, which applies by default the > 'Cumulative count cut 2% - 98%' style. > > 2. Then export the hillshaded raster (with the cumulative count style > applied) as a “Rendered Image”. > > > > I have annotated a screenshot here > https://www.dropbox.com/s/ftzk7j2bmznuvjn/raster_band_rendering.png?dl=0 > hopefully illustrating the > > 1. Improved hillshaded raster output from QGIS ('Cumulative count cut) > compared with, > > 2. gdal+mapnik output (using min-max) > > > > So, is there an approach using gdal (or similar command-line tool/app) to > achieve the “improved” hillshaded raster without the “manual” QGIS step? > > > > As I see it, my options are: > > 1. Use gdalinfo with the “-hist” option to export the histogram of the > hillshaded raster. I guess then I could maybe calculate the 2% and 98% > percentile(?) values and then manipulate the raster values using > gdal_calc.py or something else. However, I’m no statistician, so hoped > there would be an out of the box solution?! > > 2. Maybe, I could use the python api for QGIS to import the hillshade, > render, style and export back out. I’m sure this is possible, but would > require an additional python script. > > 3. Use another library or framework to achieve either of the above. I’ve > researched python’s numpy library, which maybe I could do the percentage > calculation directly on the raster. Again, potentially tricky learning > curve there… > > > > Any help or advice would greatly appreciated. If any help, the data I’m > using is here > https://www.dropbox.com/s/v0peaa3rzaqbhen/raster_band_rendering.zip?dl=0 > > > > Cheers > > > Gareth > > _______________________________________________ > gdal-dev mailing list > [email protected] > http://lists.osgeo.org/mailman/listinfo/gdal-dev >
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