Sum-of-Superellipses – A Low Parameter Model for Amplitude Spectra of Natural Images

Abstract

Abstract. Amplitude spectra of natural images look surprisingly alike. Their shape is governed by the famous 1/f power law. In this work we propose a novel low parameter model for describing these spectra. The Sum-of-Superellipses conserves their common falloff behavior while simultaneously capturing the dimensions of variation-concavity, isotropy, slope, main orientation-in a small set of meaningful illustrative parameters. We demonstrate its general usefulness in standard computer vision tasks like scene recognition and image compression.

A PSO Application in Skull Prosthesis Modelling by Superellipse

“…The [11] described its mathematical formulation and also create a superformula to be applied to plants and leaves shape identification. This theory also has been explored in many other ways, as show [12] and [13]. In our study, we are proposing to use this natural comportment in order to represent segments of human body as skull bone curvature.…”