In this paper we present a multi-scale morphological method for use in texture classification. A connected operator similar to the morphological hat-transform is defined, and two ...
Andrei Jalba, Jos B. T. M. Roerdink, Michael H. F....
This paper presents a statistical model for textures that uses a non-negative decomposition on a set of local atoms learned from an exemplar. This model is described by the varianc...
We propose a framework for exploiting dimension-reducing random projections in detection and classification problems. Our approach is based on the generalized likelihood ratio te...
Marco F. Duarte, Mark A. Davenport, Michael B. Wak...
We present an approach to multiscale image analysis. It hinges on an operative definition of texture that involves a "small region", where some (unknown) statistic is agg...
Abstract Recently proposed edge-preserving multiscale image decompositions enable artifact-free and visually appealing image editing. As the human eye is sensitive to contrast, per...