摘要
针对用遗传算法优化L滤波的权系数时必须用到原始图像和计算量大的问题,依据中心极限定理改进去除图像噪声滤波器,通过在图像上交互式的选择感兴趣区域估计混合噪声模型,并把该混合噪声模型添加到一幅较小的测试图像上,重建退化过程,然后以测试图像为目标,用遗传算法优化L滤波的权系数,并用得到的一组最优权系数结合图像的边缘信息对图像进行L滤波。仿真实验表明用该滤波器滤除图像混合噪声能得到令人满意的结果。
It based on central limit theorem estimates mixed noise model through inter-selecting region of interest in the image,and adds this mixed noise model to a small test image for rebuilding degraded process.Aiming at this test image,the genetic algorithm is used to optimize the weight coefficients of L-filter.Then the optimized weight coefficients are used in combination with image edge information to execute L-filter to the image.Pass to imitate the reality to check,result the enunciation uses that filter hybrid in addition to the picture Algorithm can get the decent result.
出处
《微计算机信息》
2010年第1期209-210,208,共3页
Control & Automation
关键词
高斯噪声
最优权系数
中心极限定理
gaussian noise
the weight coefficients
central limit theorem
