Preserving-Moment Principle-based 2-D Shannon Entropy Image Thresholding Method and its Fast Recursive Implementation
矩不变调整的二维Shannon熵图像分割及其快速实现

In order to overcome the drawbacks of the 2-D Shannon entropy image thresholding method, a preserving-moment modified Shannon entropy image thresholding method based on 2-D histogram oblictue segmentation was presented. First the two thresholding methods based on Shannon entropy were formulated by the oblique line which is perpendicular to the main diagonal; then the optimal threshold was chosen from the thresholds obtained from these methods using the preserving-moment principle, and its recursive algorithm of the method based on 2-D histogram oblique segmentation was inferred,finally the features of 2-D histogram and the algorithm were combined to get a novel recursive algorithm. Experimental results show that the proposed method's segmentation performance is much better and its running speed is about four times faster, compared with the current maximum entropy method based on 2-D oblique segmentation.