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一种改进的图像噪声滤波器的设计
Design of A Improved Filtering Algorithm
【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。
【Abstract】 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.
【Key words】 gaussian noise; the weight coefficients; central limit theorem;
- 【文献出处】 微计算机信息 ,Microcomputer Information , 编辑部邮箱 ,2010年01期
- 【分类号】TN713
- 【被引频次】1
- 【下载频次】117