We propose a novel image segmentation algorithm using piecewise smooth (PS) approximation to image. The\r\nproposed algorithm is inspired by four well-known active contour models, i.e., Chan and Vese� piecewise constant\r\n(PC)/smooth models, the region-scalable fitting model, and the local image fitting model. The four models share\r\nthe same algorithm structure to find a PC/smooth approximation to the original image; the main difference is how\r\nto define the energy functional to be minimized and the PC/smooth function. In this article, pursuing the same\r\nidea we introduce different energy functional and PS function to search for the optimal PS approximation of the\r\noriginal image. The initial function with our model can be chosen as a constant function, which implies that the\r\nproposed algorithm is robust to initialization or even free of manual initialization. Experiments show that the\r\nproposed algorithm is very appropriate for a wider range of images, including images with intensity inhomogeneity\r\nand infrared ship images with low contrast and complex background.
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