摘要: 基于L&A-PCNN模型的彩色图像混合噪声滤除算法存在算法调试须人工干预、对彩色图像滤波易出现污迹斑等问题。针对上述不足,提出一种彩色图像混合噪声自适应滤除算法。通过理论和实验分析获得L&A-PCNN模型关键参数的自适应定义和滤波算法中图像噪点的判别方法。实验结果表明,相比L&A-PCNN算法,该算法的PSNR有9%~18%的提高,处理后图像的视觉效果更好,并具有较好的自适应性和健壮性。
关键词:
脉冲耦合神经网络,
线性衰减阈值,
混合噪声,
彩色图像 ?
Abstract: Aiming at the deficiency of mixed noise removal algorithm for color images based on L&A-PCNN, this paper proposes an adaptive algorithm of mixed noise removal for color images based on improved L&A-PCNN. The adaptive setting method for key parameters and the estimation method of image pixels blurred by noises of L&A-PCNN model are gained with theoretical and experiments analysis. Experimental results show that the algorithm improves denoising performance of PSNR from 9% to 18% than L&A-PCNN algorithm, and gets a better visual effect when dealing with color images mixed noise removal, showing great adaptability and robustness.
Key words:
Pulse Coupled Neural Network(PCNN),
linear-attenuated threshold,
mixed noise,
color image
中图分类号:
王成, 黎绍发, 何凯, 涂泳秋. 基于改进PCNN的彩色图像混合噪声滤除[J]. 计算机工程, 2011, 37(01): 213-214,217.
WANG Cheng, LI Chao-Fa, HE Kai, CHU Yong-Qiu. Mixed Noise Removal for Color Images Based on Improved PCNN[J]. Computer Engineering, 2011, 37(01): 213-214,217.