Adaptive histogram equalization and its variations
Computer Vision, Graphics, and Image Processing
Multichannel Texture Analysis Using Localized Spatial Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Design and Use of Steerable Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Reflectance and texture of real-world surfaces
ACM Transactions on Graphics (TOG)
The Structure of Locally Orderless Images
International Journal of Computer Vision
Texture histograms as a function of irradiation and viewing direction
International Journal of Computer Vision
Deformable Kernels for Early Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Self Inducing Relational Distance and Its Application to Image Segmentation
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Multi-scale singularity trees: soft-linked scale-space hierarchies
Scale-Space'05 Proceedings of the 5th international conference on Scale Space and PDE Methods in Computer Vision
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In a recent work [1], Koenderink and van Doorn consider a family of three intertwined scale-spaces coined the locally orderless image (LOI). The LOI represents the image, observed at inner scale σ, as a local histogram with bin-width β, at each location, with a Gaussian-shaped region of interest of extent α. 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 consider a range of image processing tasks, including variations of adaptive histogram equalization, several methods for noise and scratch removal, texture rendering, Classification and segmentation.