Spectral Total-Variation Local Scale Signatures for Image Manipulation and Fusion

Ester Hait , Guy Gilboa (1)

1 Technion - Israel Institute of Technology [Haifa]

—We propose a unified framework for isolating, comparing and differentiating objects within an image. We rely on the recently proposed total-variation transform, yielding a continuous, multi-scale, fully edge-preserving, local descriptor, referred to as spectral total-variation local scale signatures. We show and analyze several useful merits of this framework. Signatures are sensitive to size, local contrast and composition of structures; are invariant to translation, rotation, flip and linear illumination changes; and texture signatures are robust to the underlying structures. We prove exact conditions in the 1D case. We propose several applications for this framework: saliency map extraction for fusion of thermal and optical images or for medical imaging, clustering of vein-like features and size-based image manipulation.

Mots clés: Edge Detection; Saliency; Medical Imagery; Image Segmentation ·; Index Terms—Spectral Total-Variation; Size Differentiation; Image Fusion; Thermal Imagery; Clustering

Domaines: Traitement des images [eess.IV]; Vision par ordinateur et reconnaissance de formes [cs.CV]

Ester Hait, Guy Gilboa. Spectral Total-Variation Local Scale Signatures for Image Manipulation and Fusion. 2018. ⟨hal-01722459⟩