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A scalable region-based level set method using adaptive bilateral filter for noisy image segmentation

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Abstract

Image segmentation plays an important role in the computer vision . However, it is extremely challenging due to low resolution, high noise and blurry boundaries. Recently, region-based models have been widely used to segment such images. The existing models often utilized Gaussian filtering to filter images, which caused the loss of edge gradient information. Accordingly, in this paper, a novel local region model based on adaptive bilateral filter is presented for segmenting noisy images. Specifically, we firstly construct a range-based adaptive bilateral filter, in which an image can well be preserved edge structures as well as resisted noise. Secondly, we present a data-driven energy model, which utilizes local information of regions centered at each pixel of image to approximate intensities inside and outside of the circular contour. The estimation approach has improved the accuracy of noisy image segmentation. Thirdly, under the premise of keeping the image original shape, a regularization function is used to accelerate the convergence speed and smoothen the segmentation contour. Experimental results of both synthetic and real images demonstrate that the proposed model is more efficient and robust to noise than the state-of-art region-based models.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (Grant Nos. 61472289 and 61502356) and the Natural Key Research and Development Project of China (Grant No.2016YFC0106305) and Hubei Provincial Natural Science Foundation of China(No.2019CFB797).

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Authors and Affiliations

  1. School of Computer Science, Wuhan University, Wuhan, China

    Haiping Yu, Fazhi He & Yiteng Pan

  2. City College of Wuhan University of Science and Technology, Wuhan, China

    Haiping Yu

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  1. Haiping Yu
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  2. Fazhi He
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Correspondence to Fazhi He.

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Yu, H., He, F. & Pan, Y. A scalable region-based level set method using adaptive bilateral filter for noisy image segmentation. Multimed Tools Appl 79, 5743–5765 (2020). https://doi.org/10.1007/s11042-019-08493-1

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