针对二值图像处理,为抑制噪声改善图像质量,论文提出一种利用双稳态随机共振系统实现含噪二值图像增强方法.论文首先对图像分别按行和列重采样为一维信号,并将该一维信号输入双稳态系统,通过欧拉法或龙格-库塔法迭代求解双稳态方程的输出序列,得到增强图像对行和列两个方向的偏导数,再结合该偏导数根据截断的二维泰勒公式推导出邻近像素点的值,然后对每个像素计算获得的多个值加权平均得到增强的灰度图像,对灰度图像二值分割即得到最终的复原二值图像.实验结果表明,论文算法能有效从高强度噪声中增强原二值图像,且相对于传统维纳滤波算法峰值信噪比提高了22.36％,相对于对比算法,峰值信噪比平均提高了10.8％.%For the purpose of improving the quality of binary image and restraining its noise, a binary image improving method based on bistable stochastic resonance system was proposed in this paper. Firstly, it re-sampled the image to one-dimension signal according to the row or column and inputted the re-sampled signal to bistable stochastic resonance system. When solving the bistable formula by Euler method or Runge-Kutta method, it retrieved two partial differential coefficients along row and column. Then it calculated the value of neighborhood pixel with the coefficients according to the two dimension Talyor formula. For every pixel, it was calculated 8 times and then integrated to a value with different weights each times to retrieve a gray image. To segmenting the gray image to binary image, it got the final recover result. The experiment results showed that it recovered the heavy noise polluted image in effect and improved the PSNR ( Peak Signal to Noise Rati-o) 22.36% to the traditional wiener filter method and 10. 8% to the contrast algorithm.
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