Edge-preserving multiscale image decomposition based on local extrema

Kartic Subr, Cyril Soler, Frédo Durand
2009 ACM SIGGRAPH Asia 2009 papers on - SIGGRAPH Asia '09  
a) Input (b) Fine features boosted (c) Coarse features boosted (d) Scanline plots Figure 1: Our multiscale decomposition of image (a) allows detail to be extracted based on spatial scale rather than contrast and preserves edges. (b) Boosting fine scale features increases the contrast of the pattern on the vase. (c) Boosting coarse scale contrast and suppressing fine features reduces the contrast of the pattern, while increasing the contrast of the vase with its background. (d) Scanline plots
more » ... ws indicated using arrows in (a), (b) and (c)), illustrating the effect of the two equalizations (b) and (c). The dashed lines in the plots show two examples of edges that have been preserved. Abstract We propose a new model for detail that inherently captures oscillations, a key property that distinguishes textures from individual edges. Inspired by techniques in empirical data analysis and morphological image analysis, we use the local extrema of the input image to extract information about oscillations: We define detail as oscillations between local minima and maxima. Building on the key observation that the spatial scale of oscillations are characterized by the density of local extrema, we develop an algorithm for decomposing images into multiple scales of superposed oscillations. Current edge-preserving image decompositions assume image detail to be low contrast variation. Consequently they apply filters that extract features with increasing contrast as successive layers of detail. As a result, they are unable to distinguish between highcontrast, fine-scale features and edges of similar contrast that are to be preserved.We compare our results with existing edge-preserving image decomposition algorithms and demonstrate exciting applications that are made possible by our new notion of detail.
doi:10.1145/1661412.1618493 fatcat:4bua2lnqubepbacxzlofxqyfea