Edge-preserving local fitting model for image segmentation
Guozhao Wang · Journal of Zhejiang University(Engineering Science) · 2010
Due to the fact that the segmentation accuracy of local binary fitting energy based variational model(LBF model)is highly dependent on kernel bandwidth,and it always leads to unsatisfactory segmentation results(e.g.,unnecessary contours,rough boundaries)of inhomogeneous images because of inappropriate bandwidth,an novel edge-preserving local fitting model was proposed and well adapted to segment images with intensity inhomogeneity.First,ageodesic time based kernel using spatial location and spectral gradient was defined,and it provided an adaptive geodesic neighborhood for every pixel.Then,an efficient multichannel gradient based extension combined with adjusted dissimilarity measure was enforced to segment color and multispectral images.Experimental results showed that the proposed model can remain potential edge information while using larger bandwidth,and desirable segmentation results of both gray and color images can be obtained.