Abstract. We present a new parsing framework for the line-based geometric analysis of a single image coming from a man-made environment. This parsing framework models the scene as ...
In this paper, we present a novel, threshold-free robust estimation framework capable of efficiently fitting models to contaminated data. While RANSAC and its many variants have...
A general geometrical framework for image processing is presented. We consider intensity images as surfaces in the (x I) space. The image is thereby a two dimensional surface in t...
In this paper, a novel method for learning based image super resolution (SR) is presented. The basic idea is to bridge the gap between a set of low resolution (LR) images and the ...
In this paper, we develop a spatially-variant (SV) mathematical morphology theory for gray-level signals and images in the euclidean space. The proposed theory preserves the geomet...