Second order MRF with QPBO Optimization

Second order Markov random field is dedicated to models scenes composed by plan, which is good for urban scenes for example. Maximizing a MRF energy can be formulated as minimizing a function. It is known that it is not possible to find which set of label minimize the energy related …

more ...


Graduate non convexity approach for robust fitting

newtongnc.gif

This example shows the estimation of the mean with the graduate non convexity approach using a newton optimization at each step for locally minimizing the energy. Green points are a realization of a normal distribution (vertical line shows the mean), red crosses are outliers. The blue line is the normalized …

more ...

Quadratic pseudo boolean optimization introduction

Graph-based algorithms have been used for a decade in many applications for optimization. It produces very good results. First used empirically in image processing, it has been shown that graph-based approach algorithms in image processing are a reduction of optimizing pseudo Boolean function in binary case. In pseudo Boolean optimization …

more ...

Markov Random Field Model for Single Image Defogging

logo.png

Abstract

Fog reduces contrast and thus the visibility of vehicles and obstacles for drivers. Each year, this causes traffic accidents. Fog is caused by a high concentration of very fine water droplets in the air. When light hits these droplets, it is scattered and this results in a dense white …

more ...

Vision Enhancement in Homogeneous and Heterogeneous Fog

logo.png

Abstract

One source of accidents when driving a vehicle is the presence of fog. Fog fades the colors and reduces the contrasts in the scene with respect to their distances from the driver. Various camera-based Advanced Driver Assistance Systems (ADAS) can be improved if efficient algorithms are designed for visibility …

more ...