基于多尺度多方向Gabor变换的Tsallis熵阈值分割方法

To deal with automatic threshold selection issue in non-modal, unimodal, bimodal or multimodal situations within a unified framework, a Tsallis Entropy thresholding segmentation method based on Multi-scale and multi-direction Gabor transform (MGTE) is proposed. The multi-scale product image is first obtained by the Gabor transform and then the inner and outer contour images are used to reconstruct the one-dimensional histogram from the multi-scale product image. Based on the reconstruction of the one-dimensional histogram, the Tsallis entropy calculation model is utilized to select 4 thresholds by maximizing Tsallis entropy in 4 different directions, and finally the weighted sum of the 4 thresholds is used as the final threshold. The proposed method is compared with 5 segmentation methods on 4 synthetic images and 40 real-world images. The results show that the proposed method has no advantage in computational efficiency, but its adaptability and segmentation accuracy are significantly improved.