In a recent work, Koenderink and Van Doorn consider a family of three intertwined scale-spaces coined the locally orderless image (LOI). The LOI essentially represents the image, observed at inner scale sigma, as a local histogram with bin-width beta, at each location, with a Gaussian-shape region of interest of extent alpha. LOIs form a natural and elegant extension of scale-space theory, show causal consistency and enable the smooth transition between pixels, histograms and isophotes. The aim of this work is to demonstrate the wide applicability and versatility of LOIs. We present applications for a range of image processing tasks, including new non-linear diffusion schemes, adaptive histogram equalization and variations, several methods for noise and scratch removal, texture rendering, classiffication and segmentation.