Image segmentation using optimal and hierarchical piecewise-constant approximations
Mikhail Vyacheslavovich Kharinov · Pattern Recognition and Image Analysis · 2014
The problem of approaching optimal image approximations using quasi-optimal hierarchical approximations, which are close to the optimal ones in terms of the total squared error, is considered. The problem is solved using algorithms for merging and dividing pixel clusters. The algorithms are based on elementary formulas. Information encoded in the image is proposed to be described, based on quasi-optimal approximations, using the invariant isomorphic image representation. The definition of the integer quantity of information is given, and the comparison of the integer estimate with the classical estimates in terms of R. Hartley and K. Shannon is performed. The experimental study of the properties of quasi-optimal hierarchical approximations, which are characteristic and uncharacteristic of nonhierarchical optimal image approximations, is carried out.