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Fast recursive algorithm for two-dimensional Tsallis entropy thresholding method 被引量:2
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作者 Tang Yinggan Di Qiuyan Guan Xinping 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2009年第3期619-624,共6页
Recently, a two-dimensional (2-D) Tsallis entropy thresholding method has been proposed as a new method for image segmentation. But the computation complexity of 2-D Tsallis entropy is very large and becomes an obst... Recently, a two-dimensional (2-D) Tsallis entropy thresholding method has been proposed as a new method for image segmentation. But the computation complexity of 2-D Tsallis entropy is very large and becomes an obstacle to real time image processing systems. A fast recursive algorithm for 2-D Tsallis entropy thresholding is proposed. The key variables involved in calculating 2-D Tsallis entropy are written in recursive form. Thus, many repeating calculations are avoided and the computation complexity reduces to O(L2) from O(L4). The effectiveness of the proposed algorithm is illustrated by experimental results. 展开更多
关键词 image segmentation THRESHOLDING Tsallis entropy fast recursive algorithm
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An Effective Method of Threshold Selection for Small Object Image
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作者 吴一全 吴加明 占必超 《Defence Technology(防务技术)》 SCIE EI CAS 2011年第4期235-242,共8页
The image segmentation difficulties of small objects which are much smaller than their background often occur in target detection and recognition. The existing threshold segmentation methods almost fail under the circ... The image segmentation difficulties of small objects which are much smaller than their background often occur in target detection and recognition. The existing threshold segmentation methods almost fail under the circumstances. Thus, a threshold selection method is proposed on the basis of area difference between background and object and intra-class variance. The threshold selection formulae based on one-dimensional (1-D) histogram, two-dimensional (2-D) histogram vertical segmentation and 2-D histogram oblique segmentation are given. A fast recursive algorithm of threshold selection in 2-D histogram oblique segmentation is derived. The segmented images and processing time of the proposed method are given in experiments. It is compared with some fast algorithms, such as Otsu, maximum entropy and Fisher threshold selection methods. The experimental results show that the proposed method can effectively segment the small object images and has better anti-noise property. 展开更多
关键词 information processing small infrared target detection image segmentation threshold selection 2-D histogram oblique segmentation fast recursive algorithm
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