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Effect of Modified Wiener Algorithm on Noise Models

机译:改进的维纳算法对噪声模型的影响

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The restoration of images degraded by linear motion blur and additive noise is examined. Previously, restoration of degraded images due to linear motion blur and Gaussian noise using Modified Wiener algorithm was applied successfully. However, considering the fact that there are other types of Noise models, the stability of the performance of the algorithm need be ascertained. In this paper, the effect of Modified Wiener algorithm on the restoration of degraded images by linear motion blur and three different noise models was carried out. Evaluation was done using the same three quantitative performance measures: Root Mean Square Error (RMSE), Signal- to-Noise Ratio (SNR) and Peak Signal-to-Noise Ratio (PSNR), with RMSE and SNR as the objective measurement. Results showed the consistency of the algorithm.
机译:检查了由于线性运动模糊和附加噪声而退化的图像的恢复。以前,已经成功地应用了使用改进的Wiener算法恢复由于线性运动模糊和高斯噪声而导致的退化图像的恢复。但是,考虑到存在其他类型的噪声模型这一事实,需要确定算法性能的稳定性。本文研究了改进的维纳算法对线性运动模糊和三种不同噪声模型对退化图像的恢复效果。使用相同的三个定量性能指标进行评估:均方根误差(RMSE),信噪比(SNR)和峰值信噪比(PSNR),以RMSE和SNR作为客观指标。结果表明算法的一致性。

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