Factory method, create instance of FastGlobalSmootherFilter and execute the initialization routines

obj = cv.FastGlobalSmootherFilter(guide)
obj = cv.FastGlobalSmootherFilter(guide, 'OptionName',optionValue, ...)

Input

• guide image serving as guide for filtering. It should have 8-bit depth and either 1 or 3 channels.

Options

• Lambda parameter defining the amount of regularization. default 100.0
• SigmaColor parameter, that is similar to color space sigma in cv.bilateralFilter. default 5.0
• LambdaAttenuation internal parameter, defining how much lambda decreases after each iteration. Normally, it should be 0.25. Setting it to 1.0 may lead to streaking artifacts. default 0.25
• NumIter number of iterations used for filtering, 3 is usually enough. default 3

For more details about Fast Global Smoother parameters, see the original paper [Min2014]. However, please note that there are several differences. Lambda attenuation described in the paper is implemented a bit differently so do not expect the results to be identical to those from the paper; SigmaColor values from the paper should be multiplied by 255.0 to achieve the same effect. Also, in case of image filtering where source and guide image are the same, authors propose to dynamically update the guide image after each iteration. To maximize the performance this feature was not implemented here.