The goal ofcatsim is to provide a similarity measure for binary or categorical images in either 2D or 3D similar to theMS-SSIM index for color images. Suppose you have a ground truth segmentation of some image that has been segmented into regions - perhaps a brain scan with different types of tissues or a map with different types of terrain - and a segmentation produced by some classification method. Comparing the two pixel-by pixel (or voxel-by-voxel) might work well, but a method that captures structural similarities might work better for your purposes. MS-SSIM is an image comparison metric that tries to match the assessment of the human visual system by considering structural similarities across multiple scales. CatSIM applies a similar logic in the case of 2-D and 3-D binary and multicategory images, such as might be found in image segmentation or classification problems.
Installation
You can install the released version of catsim fromCRAN with:
install.packages("catsim")#### or the dev version with:#devtools::install_github("gzt/catsim")Usage
If you have two images,x andy, the simplest method of comparing them is:
By default, this performs 5 levels of downsampling and uses Cohen’s kappa as the local similarity metric on11 x 11 windows for a 2-dimensional image and5 x 5 x 5 windows for a 3-D image. Those can be adjusted using thelevels,method, andwindow arguments.
Please note that thecatsim project is released with aContributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
