Background: The presence of speckle noise in synthetic aperture radar (SAR) images
makes the images of low quality in terms of textural features and spatial resolution which are
required for processing issues such as image classification and clustering. Already, there are many
adaptive filters to remove noise in SAR images. ENVI software is a fully applicable tool for this
purpose which has a good library including several filters in the classes of adaptive, orderstatistics
and non-linear filters.
Methods: In this study, the toolbox of ENVI is reviewed, analyzed and then numerically evaluated
based on several single-band images along with multi-band polarimetric SAR (Pol-SAR) images
achieved from SAR sensors such as TerraSAR-X. For evaluation, two metrics including
equivalent number of looks (ENL) and edge preservation index (EPI) are used which show the
ability of the filters in preserving jointly spatial/textural features based on general information and
edges quality, respectively.
Results: It is notable that both metrics illustrate that some classic filters are better in comparison
to newer filters.
Conclusion: The experiments can help us in selecting a better filter towards our aims. In this
respect, attention to the results of commercial filters of ENVI software and their analysis can
guide us to find the best case in order to process commercial data of SAR sensors in the
applications of environmental monitoring, geo-science studies, industrial usages and so on.