Modeling and Optimization in Image Analysis
1.1. Modeling at the source of image analysis and synthesis
From its first days, image analysis has been facing the problem of modeling. Pioneering works on contour detection led their authors to refer to explicit models of edges and noise [PET 91], which they used as a conceptual basis in order to build their algorithms. With an opposite approach to these phenomenological models, a physical model of light diffusion on surfaces has been used as the basis for Horn’s works [HOR 75] on shape from shading. More generally, a phenomenological model aims at describing a directly computable property of the geometric configurations of gray levels on an image; the physical model then tries to use the knowledge corpus of physics, or even sometimes to create an ad-hoc conceptual system, as we will see later. Between these two extremes, there is a large number of approaches to modeling. Here, we shall try to illustrate them using some examples.
It is important to first show the links between image analysis and synthesis. For a number of years, these two domains have been undergoing largely independent development processes. In spite of their conceptual similarity, they have been dealt with by two separate scientific communities, with different origins and centers of interest, which did not address the same applications. Robotics is one of the few fields of application that has played an important role in moving them closer to one another. ...