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文件名称：RSF模型的python实现
文件大小：2KB
文件格式：PY
更新时间：2022-04-21 14:21:46
图像分割
李老师的rsf模型的python代码Intensity inhomogeneities often occur in real-world
images and may cause considerable difficulties in image segmenta-
tion. In order to overcome the difficulties caused by intensity inho-
mogeneities, we propose a region-based active contour model that
draws upon intensity information in local regions at a controllable
scale. A data fitting energy is defined in terms of a contour and two
fitting functions that locally approximate the image intensities on
the two sides of the contour. This energy is then incorporated into
a variational level set formulation with a level set regularization
term, from which a curve evolution equation is derived for energy
minimization. Due to a kernel function in the data fitting term, in-
tensityinformation inlocal regions isextracted toguidethemotion
of the contour, which thereby enables our model to cope with in-
tensity inhomogeneity. In addition, the regularity of the level set
function is intrinsically preserved by the level set regularization
term to ensure accurate computation and avoids expensive reini-
tialization of the evolving level set function. Experimental results
for synthetic and real images show desirable performances of our
method.