Image Thresholding Based on Two-Dimensional Arimoto Entropy
ZHUO Wen, CAO Zhi-Guo, XIAO Yang
State Key Laboratory for Muti-Spectral Information Processing Technology, Institute of Pattern Recognition and Artificial Intelligence, Huazhong University of Science and Technology, Wuhan 430074
Abstract A thresholding technique is proposed based on two-dimensional Arimoto entropy. Firstly, a two-dimensional histogram is determined by the gray value and the local average gray value of the pixels. Then, the two-dimensional Arimoto entropy is obtained from the two-dimensional histogram. The pair of gray values which makes the two-dimensional Arimoto entropy largest is the thresholding. By introducing in a two-dimensional joint power-probability distribution, a fast algorithm is proposed. The fast algorithm speeds up the implementation and makes the method suitable to real-time systems. Experiments indicate that the thresholding method based on two-dimensional Arimoto entropy gives a steady performance and it is better than the methods based on Renyi entropy and Shannon entropy.
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2009, Vol. 22 
