关键词: 图像分割, 小波变换, 直方图分析, BF算法

Abstract: Image noise may have a direct influence on the quality of image segmentation. In order to distinguish targets from noise-polluted image quickly and accurately, this paper proposes a method based on histogram preprocessing and BF algorithm for noisy image segmentation. In this method, discrete wavelet transform is used to suppress the noise in the image firstly. Secondly, the histogram feature of the denoised image is analyzed to shrink the distribution range of the optimal threshold. Then, two-dimensional Otsu is selected as the segmentation objective function, and bacterial foraging algorithm is employed to find the optimal threshold in parallel. Experimental results show that this method performs better than some other methods based on swarm intelligence like genetic algorithm, artificial fish swarm algorithm as far as convergence speed, stability and segmentation effect are concerned.

Key words: image segmentation, wavelet transform, histogram analysis, bacterial foraging algorithm