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Fuzzy STUDENT’S T-Distribution Model Based on Richer Spatial Combination by Tao Lei; Xiaohong Jia; Dinghua Xue; Qi Wang; Hongying Meng; Asoke K. Nandi is a Computer Science article available to read on EtoBox.

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Fuzzy c-means (FCM) algorithms with spatial information have been widely applied in the field of image segmentation. However, most of them suffer from two challenges. One is that introduction of fixed or adaptive single neighboring information with narrow receptive field limits contextual constraints leading to clutter segmentations. The other is that incorporation of superpixels with wide receptive field enlarges spatial coherency leading to block effects. To address these challenges, we propose fuzzy Student's t-distribution model based on richer spatial combination (FRSC) for image segmentation. In this Paper, we make two significant contributions. The first is that both narrow and wide receptive fields are integrated into the objective function of FRSC, which is convenient to mine image features and distinguish local difference. The second is that the rich spatial combination under Student's t-distribution ensures that spatial information is introduced into the updated parameters of FRSC, which is helpful in finding a balance between the noise-immunity and detail-preservation. Experimental results on synthetic and publicly available images, further demonstrate that the proposed

Who reads Fuzzy STUDENT’S T-Distribution Model Based on Richer Spatial Combination?

Author

Tao Lei; Xiaohong Jia; Dinghua Xue; Qi Wang; Hongying Meng; Asoke K. Nandi

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Published

2022

Language

EN

Field

Computer Science (Physical Sciences)