Pyramid segmentation parameters estimation based on image total variation

In this paper, a procedure for estimating input parameters (thresholds) of the pyramid segmentation algorithm based on image total variation is proposed. Image segmentation is a crucial part of low and high level digital image analysis. Among others, pyramid segmentation algorithm depends on input parameters to be provided as an a-priori known input data. In the case when one single image is segmented, those parameters can be determined interactively. In our work, a database of images were to be segmented in a given time constraints what requires an automatic estimation of segmentation input parameters. In order to achieve this, a digital image total variance is defined and an estimation formula based on image total variance is evolved. The proposed parameters estimation formulas are experimentally evaluated.