A Guided Edge-Aware Smoothing-Sharpening Filter Based on Patch Interpolation Model and Generalized Gamma Distribution

Smoothing and sharpening are two fundamental image processing operations. The latter is usually related to the former through unsharp masking algorithm. In this paper, we develop a new type of filter which performs smoothing or via tuning parameter. development based on (1) Laplacian-based formulation unifies operations, (2) patch interpolation model similar that used in guided provides edge-awareness capability, (3) generalized Gamma distribution as prior for parameter estimation. We have conducted detailed studies properties versions proposed (self-guidance external guidance). also experiments demonstrate applications filter. self-guidance case, developed adaptive algorithms texture, depth blurriness information extracted from an image. Applications include enhancing human face images, producing shallow field effects, focus-based enhancement, seam carving. guidance combining flash no-flash images multi-spectral using panchromatic