Variational image processing
= Variational image processing
A variational model balances agreement with observed data against a regularity or geometric penalty. Examples include <total variation denoising>, the <relaxed graph-area functional>, and the <Mumford–Shah functional>. Convex penalties support unique reconstruction, while segmentation energies can have multiple competing partitions.