1. A computer-implemented feature extraction method for classifying pixels of a digitized image, the method to be performed by a system comprising at least one processor and at least one memory, the method comprising: generating a plurality of characterized pixels from a digitized image; generating a plurality of classification models by associating features of the plurality of characterized pixels with labels of a plurality of ground truths, wherein each of the plurality of ground truths is associated with a respective one of a plurality of image classifications; determining by the system a plurality of confidence maps based on the plurality of classification models, wherein the confidence maps contain information representing a likelihood of each pixel in the digitized image belonging to one of the plurality of image classifications; and iteratively improving the plurality of classification models by (a) extracting a plurality of contextual image feature vectors from the most-recently generated plurality of confidence maps, (b) updating the plurality of classification models based on the most-recently extracted plurality of contextual image feature vectors, and performing steps a and b for a threshold number of iterations; and outputting by the system a plurality of final classification models that classify part or all of the pixels of the digitized image.