Sparse Multiscale Pacthes for Image Processing

Section 2 is indeed devoted to unsupervised learning techniques for natural image patches, including dictionary learning; Sections 3 and 4 present a large number of applications

These methods consist of the characterization of canvas, the analysis of multispectral imagery of a painting and even the objective quantification of the style of a particular

For the tests, four algorithms were chosen: the weighted linear filter, reverse gradient filter, edge detection Canny’s filter, and morphology processing filter erosion.. An example

The methodology is illustrated on the line following problem of a sailboat and then validated on an actual experiment where an actual sailboat robot, named Vaimos, sails

Abstract. In this work we are going to set up a new relationship be- tween the L-fuzzy Concept Analysis and the Fuzzy Mathematical Mor- phology. Specifically we prove that the problem

One of its conclusion is that a macro data-flow representation of skeleton-based parallel programs is probably the best choice, because it can be associated with a wide spectrum

This work is a contribution to the image process- ing field because the modeling of the formulation al- lows to give prominence to the knowledge used in the development of

Half size padding (‘same’ size) Unit stride. No zero padding,