Calculus of Variation combined with Differential Geometry as tools of modelling and solving problems in image processing and computer vision were introduced in the late 80's and the 90s of the 20th century. The beginning of an extensive work in these directions was marked by works such as Geodesic Active Contours (GAC), the Beltrami framework, level set method of Osher and Sethian the works of Charpiat et al. and the works by Chan and Vese to name just a few. In many cases the optimization of these functional are done by the gradient descent method via the calculation of the Euler-Lagrange equations. Straightforward use of the resulted EL equations in the gradient descent scheme leads to non-geometric and in some cases non sensical equations. It is costumary to modify these EL equations or even the functional itself in order to obtain geometric and/or sensical equations. The aim of this note is to point to the correct way to derive the EL and the gradient descent equations such that the resulted gradient descent equation is geometric and makes sense.
翻译:在20世纪80年代末和90年代,开始在这些方向上广泛开展工作的标志是大地测量活性光谱(GAC)、Beltrami框架、Osher和Sethian的定级方法、Charpiat等人等人的作品以及Chan和Vese的作品,这些功能只是其中几个名称。在许多情况下,这些功能的优化是通过梯度下降法,通过计算Euler-Lagrange方程式来完成的。在梯度下降公式中直接前方使用最终产生的EL方程式,导致非地貌化和在某些情况下非感官方程式。修改这些EL方程式,甚至功能本身,以获得几何和/或感官方程式,是合算成本的。本说明的目的是指出正确的方法,得出EL和梯度血基方程式,使结果的梯度下降方程式具有几何和感知意义。