Calculates the superpixel segmentation on a given image with the initialized parameters in the object

obj.iterate(img)
obj.iterate(img, 'OptionName',optionValue, ...)

Input

• img Input image. Supported formats: uint8, uint16, single. Image size & number of channels must match with the initialized image size & channels with the constructor. It should be in HSV or Lab color space. Lab is a bit better, but also slower.

Options

• NumIterations Number of iterations. Higher number improves the result. default 4

The function computes the superpixels segmentation of an image with the parameters initialized with the constructor. The algorithms starts from a grid of superpixels and then refines the boundaries by proposing updates of blocks of pixels that lie at the boundaries from large to smaller size, finalizing with proposing pixel updates. An illustrative example can be seen below.

This function can be called again for other images without the need of initializing the algorithm with constructor. This save the computational cost of allocating memory for all the structures of the algorithm.