Feature Description

Performs binary classification on a single image data using a model file. The data format must match that specified by the model file. The returned result type is a raster dataset (RasterRDD).

Binary classification of imagery involves using deep learning algorithms to determine whether pixels in the image belong to the class of interest. It is commonly used to extract distinct single classes such as roads, rivers, and buildings. The result type is a raster dataset (RasterRDD), with pixel values of 1 and 0, where 1 indicates that the pixel belongs to the class of interest.

The following figure shows the original image overlaid with the binary classification analysis result:

Parameter description