You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
For this reason, we should consider a new function sits_sar_texture() that implements the texture measures described in Table 2 of the above paper.
Associated sits API function sits_sar_texture(cube, measure, output_dir, multicores, memzise) where:
cube is a SAR image data cube and measure is one of grey-level co-occurence matrices (GLCM) metrics.
The text was updated successfully, but these errors were encountered:
@gilbertocamara you are welcome.
I think it would be great to have one high quality and comprehensive package for GLCM textures than a few ones only having some measures...
Describe the new API function requested
Reccent papers on deforestation alerts, as for example "How textural features can improve SAR-based tropical forest disturbance mapping" indicate that some of the Haralick texture metrics based on co-occurence matrix can improve their accuracy.
For this reason, we should consider a new function
sits_sar_texture()
that implements the texture measures described in Table 2 of the above paper.Associated sits API function
sits_sar_texture(cube, measure, output_dir, multicores, memzise)
where:cube is a SAR image data cube and
measure
is one of grey-level co-occurence matrices (GLCM) metrics.The text was updated successfully, but these errors were encountered: